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  • 51. Astruc, Marine
    et al.
    Malm, Patrik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kumar, Rajesh
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Cluster detection and field-of-view quality rating: Applied to automated Pap-smear analysis2013In: Proc. 2nd International Conference on Pattern Recognition Applications and Methods, SciTePress, 2013, p. 355-364Conference paper (Refereed)
    Abstract [en]

    Automated cervical cancer screening systems require high resolution analysis of a large number of epithelial cells, involving complex algorithms, mainly analysing the shape and texture of cell nuclei. This can be a very time consuming process. An initial selection of relevant fields-of-view in low resolution images could limit the number of fields to be further analysed at a high resolution. In particular, the detection of cell clusters is of interest for nuclei segmentation improvement, and for diagnostic purpose, malignant and endometrial cells being more prone to stick together in clusters than other cells. In this paper, we propose methods aiming at evaluating the quality of fields-of-view in bright-field microscope images of cervical cells. The approach consists in the construction of neighbourhood graphs using the nuclei as the set of vertices. Transformations are then applied on such graphs in order to highlight the main structures in the image. The methods result in the delineation of regions with varying cell density and the identification of cell clusters. Clustering methods are evaluated using a dataset of manually delineated clusters and compared to a related work.

  • 52.
    Augustsson, Louise
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Study and Analysis of Convolutional Neural Networks for Pedestrian Detection in Autonomous Vehicles2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The automotive industry is heading towards more automation. This puts high demands on many systems like Pedestrian Detection Systems. Such systems need to operate in real time with high accuracy and in embedded systems with limited power, memory resources and compute power. This in turn puts high demands on model size and model design. Lately Convolutional Neural Networks (ConvNets) have dominated the field of object detection and therefore it is reasonable to believe that they are suited for pedestrian detection as well. Therefore, this thesis investigates how ConvNets have been used for pedestrian detection and how such solutions can be implemented in embedded systems on FPGAs (Field Programmable Gate Arrays). The conclusions drawn are that ConvNets indeed perform well on pedestrian detection in terms of accuracy but to a cost of large model sizes and heavy computations. This thesis also comes up with a design proposal of a ConvNet for pedestrian detection with the implementation in an embedded system in mind. The proposed network performs well on pedestrian classification and the performance looks promising for detection as well, but further development is required.

  • 53.
    Avenel, Christophe
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Carlbom, Ingrid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Blur detection and visualization in histological whole slide images2015In: Proc. 10th International Conference on Mass Data Analysis of Images and Signals, Leipzig, Germany: IBaI , 2015Conference paper (Refereed)
    Abstract [en]

    Digital pathology holds the promise of improved workflow and also of the use of image analysis to extract features from tissue samples for quantitative analysis to improve current subjective analysis of, for example, cancer tissue. But this requires fast and reliable image digitization. In this paper we address image blurriness, which is a particular problem with very large images or tissue micro arrays scanned with whole slide scanners, since autofocus methods may fail when there is a large variation in image content. We introduce a method to detect, quantify and dis-play blurriness from whole slide images (WSI) in real-time. We describe a blurriness measurement based on an ideal high pass filter in the frequency domain. In contrast with other method our method does not require any prior knowledge of the image content, and it produces a continuous blurriness map over the entire WSI. This map can be displayed as an overlay of the original data and viewed at different levels of magnification with zoom and pan features. The computation time for an entire WSI is around 5 minutes on an average workstation, which is about 180 times faster than existing methods.

  • 54.
    Avenel, Christophe
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fortin, Pierre
    Gouicem, Mourad
    Zaidi, Samia
    Solving the Table Maker's Dilemma on current SIMD architectures2016In: Scalable Computing: Practice and Experience, ISSN 1895-1767, E-ISSN 1895-1767, Vol. 17, no 3, p. 237-250Article in journal (Refereed)
  • 55.
    Avenel, Christophe
    et al.
    CADESS Med AB, Uppsala, Sweden.
    Tolf, Anna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical and experimental pathology.
    Dragomir, Anca
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Clinical and experimental pathology.
    Carlbom, Ingrid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. CADESS Med AB, Uppsala, Sweden.
    Glandular Segmentation of Prostate Cancer: An Illustration of How the Choice of Histopathological Stain Is One Key to Success for Computational Pathology2019In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 7, article id 125Article in journal (Refereed)
    Abstract [en]

    Digital pathology offers the potential for computer-aided diagnosis, significantly reducing the pathologists' workload and paving the way for accurate prognostication with reduced inter-and intra-observer variations. But successful computer-based analysis requires careful tissue preparation and image acquisition to keep color and intensity variations to a minimum. While the human eye may recognize prostate glands with significant color and intensity variations, a computer algorithm may fail under such conditions. Since malignancy grading of prostate tissue according to Gleason or to the International Society of Urological Pathology (ISUP) grading system is based on architectural growth patterns of prostatic carcinoma, automatic methods must rely on accurate identification of the prostate glands. But due to poor color differentiation between stroma and epithelium from the common stain hematoxylin-eosin, no method is yet able to segment all types of glands, making automatic prognostication hard to attain. We address the effect of tissue preparation on glandular segmentation with an alternative stain, Picrosirius red-hematoxylin, which clearly delineates the stromal boundaries, and couple this stain with a color decomposition that removes intensity variation. In this paper we propose a segmentation algorithm that uses image analysis techniques based on mathematical morphology and that can successfully determine the glandular boundaries. Accurate determination of the stromal and glandular morphology enables the identification of the architectural pattern that determine the malignancy grade and classify each gland into its appropriate Gleason grade or ISUP Grade Group. Segmentation of prostate tissue with the new stain and decomposition method has been successfully tested on more than 11000 objects including well-formed glands (Gleason grade 3), cribriform and fine caliber glands (grade 4), and single cells (grade 5) glands.

  • 56.
    Axelsson, Anton
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Context: The abstract term for the concrete2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis deals with the term 'context' and the aim has been to reason about the term in order to see whether it is possible to reach a satisfactory understanding of the concept. But the thesis is also a journey into human reasoning and conveys a certain view of human cognition. It aims to synthesise results of studies within psychology, cognitive science, anthropology, and human-computer interaction. My understanding is that context is not something we are a part of, but rather something we create mentally in relation a specific goal. Determination of something ambiguous thus comes from top-down processes related to a goal. I believe context has been wrongly interpreted in HCI as that which a user is situated in and which a product is being used in. I suggest instead a separation between the user environment and the user context.

    List of papers
    1. Scaffolding executive function capabilities via play-&-learn software for preschoolers
    Open this publication in new window or tab >>Scaffolding executive function capabilities via play-&-learn software for preschoolers
    2016 (English)In: Journal of Educational Psychology, ISSN 0022-0663, E-ISSN 1939-2176, Vol. 108, no 7, p. 969-981Article in journal (Refereed) Published
    Abstract [en]

    Educational software in the form of games or so called "computer assisted intervention" for young children has become increasingly common receiving a growing interest and support. Currently there are, for instance, more than 1,000 iPad apps tagged for preschool. Thus, it has become increasingly important to empirically investigate whether these kinds of software actually provide educational benefits for such young children. The study presented in the present article investigated whether preschoolers have the cognitive capabilities necessary to benefit from a teachable-agent-based game of which pedagogical benefits have been shown for older children. The role of executive functions in children's attention was explored by letting 36 preschoolers (3;9-6;3 years) play a teachable-agent-based educational game and measure their capabilities to maintain focus on pedagogically relevant screen events in the presence of competing visual stimuli. Even though the participants did not succeed very well in an inhibition pretest, results showed that they nonetheless managed to inhibit distractions during game-play. It is suggested that the game context acts as a motivator that scaffolds more mature cognitive capabilities in young children than they exhibit during a noncontextual standardized test. The results further indicate gender differences in the development of these capabilities.

    Keywords
    inhibition; attention; teachable agents; eye tracking; learning by teaching
    National Category
    Human Computer Interaction Learning
    Identifiers
    urn:nbn:se:uu:diva-275524 (URN)10.1037/edu0000099 (DOI)000385436300005 ()
    Projects
    Cognition, Communication, and Learning (CCL)
    Funder
    Swedish Research Council, 437-2014-6735
    Available from: 2016-01-18 Created: 2016-02-04 Last updated: 2018-01-10Bibliographically approved
    2. Collegial verbalisation — the value of an independent observer: an ecological approach
    Open this publication in new window or tab >>Collegial verbalisation — the value of an independent observer: an ecological approach
    2015 (English)In: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 16, no 5, p. 474-494Article in journal (Refereed) Published
    National Category
    Human Computer Interaction Psychology (excluding Applied Psychology)
    Identifiers
    urn:nbn:se:uu:diva-249009 (URN)10.1080/1463922X.2015.1027322 (DOI)
    Available from: 2015-04-07 Created: 2015-04-09 Last updated: 2019-01-09Bibliographically approved
    3. Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    Open this publication in new window or tab >>Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    2018 (English)In: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 19, no 1, p. 101-117Article in journal (Refereed) Published
    Abstract [en]

    Introducing automation in a human-machine system changes the tasks performed by human operators. It is difficult to analyse systems for which there are no experienced operators. This issue emerged within a project with the aim to develop a human–machine interface for a highly automated long-haul vehicle. To handle the problem, a formative strategies analysis method with promises to enable desktop analyses through predefined strategy categories was adopted. The method was used to investigate strategies for controlling the future long haul vehicle by conducting workshops with today's drivers. The method was shown to be a valuable asset in eliciting strategies for revolutionary design.

    Keywords
    Cognitive work analysis, strategies analysis, automation, revolutionary systems design, long haul trucks
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-292799 (URN)10.1080/1463922X.2017.1278805 (DOI)000428728900006 ()
    Projects
    MODAS
    Funder
    VINNOVA, 2012-03678
    Available from: 2017-01-27 Created: 2016-05-09 Last updated: 2019-01-09Bibliographically approved
  • 57.
    Axelsson, Anton
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Experience and Visual Expertise: A First Look at Eye Behaviour in Train Traffic ControlIn: Article in journal (Refereed)
    Abstract [en]

    The present study investigated differences in visual expertise across levels of proficiency in train traffic control during a simulated scenario. Eye tracking metrics found to correlate with expertise reported in a meta-analysis on visual expertise were used. The aim of the study was to investigate whether the same results found in the meta-study could be obtained in the less controlled and dynamic work environment of train traffic control. Studies of this character are rare and also notoriously difficult to conduct due to a high level of potential noise. Results of the study indicates that eye behaviour seemed to correlate with years of experience also in a more naturalistic setting, but it did not correlate with expert ranking by instructors or a post-hoc measure of proactivity in task performance. A discussion is provided where a delineation of experience and expertise is made in light of differences between eye movement behaviour and cognitive aspects of problem-solving.

  • 58.
    Axelsson, Anton
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Knowledge elicitation as abstraction of purposive behaviour2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Researchers use knowledge elicitation methods to document expert knowledge for the primary purpose of understanding cognitive processes and with this understanding, technical solutions to resolve human factors issues can be produced. This dissertation offers a novel perspective on knowledge elicitation as an abstraction process. Such a theoretical framework has emerged by consolidating the ecological approach of Brunswikian psychology with the ideas of tacit and personal knowledge of Polanyian epistemology. Traditionally, knowledge elicitation has been considered an extraction process in which knowledge can be readily transferred from one individual to another. Here, this traditional position is rejected in favour of Polanyi’s premise that much of the knowledge individuals possess is tacit in nature, which implies that it cannot be documented easily, expressed in explicit form or explained. In this dissertation, knowledge is characterised as a personal process of knowing, highlighting context as a subjective knowledge structure of personal experiences that is formulated implicitly and indirectly over time through a dynamic interaction with the environment. Therefore, tacit knowledge cannot be articulated or shared; however, learners can be inspired by observing other individuals' purposive (i.e., goal-directed) behaviours and thus shape their own tacit knowledge once they practise the observed skills and develop conceptual understanding through reasoning about the learning process. Knowledge elicitation thereby makes use of observations, questions, or more structured process tracing methods in environments familiar to the observed individuals to elicit purposive behaviour from them. Accordingly, functional descriptions can be produced in this process that further conceptual understanding of a particular domain. Knowledge elicitation procedures are a powerful set of methods for reaching such functional descriptions. Moreover, by understanding the resulting knowledge elicitation data as an abstraction derived from multiple collection points in the same environment, the focus shifts from purely subjective mental constructs to the impact of environmental constraints.

    List of papers
    1. Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    Open this publication in new window or tab >>Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    2018 (English)In: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 19, no 1, p. 101-117Article in journal (Refereed) Published
    Abstract [en]

    Introducing automation in a human-machine system changes the tasks performed by human operators. It is difficult to analyse systems for which there are no experienced operators. This issue emerged within a project with the aim to develop a human–machine interface for a highly automated long-haul vehicle. To handle the problem, a formative strategies analysis method with promises to enable desktop analyses through predefined strategy categories was adopted. The method was used to investigate strategies for controlling the future long haul vehicle by conducting workshops with today's drivers. The method was shown to be a valuable asset in eliciting strategies for revolutionary design.

    Keywords
    Cognitive work analysis, strategies analysis, automation, revolutionary systems design, long haul trucks
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-292799 (URN)10.1080/1463922X.2017.1278805 (DOI)000428728900006 ()
    Projects
    MODAS
    Funder
    VINNOVA, 2012-03678
    Available from: 2017-01-27 Created: 2016-05-09 Last updated: 2019-01-09Bibliographically approved
    2. Collegial verbalisation — the value of an independent observer: an ecological approach
    Open this publication in new window or tab >>Collegial verbalisation — the value of an independent observer: an ecological approach
    2015 (English)In: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 16, no 5, p. 474-494Article in journal (Refereed) Published
    National Category
    Human Computer Interaction Psychology (excluding Applied Psychology)
    Identifiers
    urn:nbn:se:uu:diva-249009 (URN)10.1080/1463922X.2015.1027322 (DOI)
    Available from: 2015-04-07 Created: 2015-04-09 Last updated: 2019-01-09Bibliographically approved
    3. On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise
    Open this publication in new window or tab >>On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise
    2018 (English)In: Journal of Applied Research in Memory and Cognition, ISSN 2211-3681, E-ISSN 2211-369X, Vol. 7, no 1, p. 51-59Article in journal (Refereed) Published
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-352734 (URN)10.1016/j.jarmac.2017.12.004 (DOI)000429489400010 ()
    Funder
    Swedish Transport Administration
    Available from: 2018-03-03 Created: 2018-06-07 Last updated: 2019-01-09Bibliographically approved
    4. Experience and Visual Expertise: A First Look at Eye Behaviour in Train Traffic Control
    Open this publication in new window or tab >>Experience and Visual Expertise: A First Look at Eye Behaviour in Train Traffic Control
    (English)In: Article in journal (Refereed) Submitted
    Abstract [en]

    The present study investigated differences in visual expertise across levels of proficiency in train traffic control during a simulated scenario. Eye tracking metrics found to correlate with expertise reported in a meta-analysis on visual expertise were used. The aim of the study was to investigate whether the same results found in the meta-study could be obtained in the less controlled and dynamic work environment of train traffic control. Studies of this character are rare and also notoriously difficult to conduct due to a high level of potential noise. Results of the study indicates that eye behaviour seemed to correlate with years of experience also in a more naturalistic setting, but it did not correlate with expert ranking by instructors or a post-hoc measure of proactivity in task performance. A discussion is provided where a delineation of experience and expertise is made in light of differences between eye movement behaviour and cognitive aspects of problem-solving.

    Keywords
    visual expertise, eye tracking, experience, train traffic control, rail human factors
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-372696 (URN)
    Funder
    Swedish Transport Administration
    Available from: 2019-01-08 Created: 2019-01-08 Last updated: 2019-01-09
  • 59.
    Axelsson, Anton
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    A. Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise2018In: Journal of Applied Research in Memory and Cognition, ISSN 2211-3681, E-ISSN 2211-369X, Vol. 7, no 1, p. 51-59Article in journal (Refereed)
  • 60.
    Axelsson, Anton
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Andersson, Richard
    IT Univ Copenhagen, Eye Informat Grp, Copenhagen, Denmark; Lund Univ, Lund Univ Cognit Sci, S-22100 Lund, Sweden.
    Gulz, Agneta
    Lund Univ, Lund Univ Cognit Sci, S-22100 Lund, Sweden; Linkoping Univ, Dept Comp & Informat Sci, Cognit & Interact Res Grp, S-58183 Linkoping, Sweden.
    Scaffolding executive function capabilities via play-&-learn software for preschoolers2016In: Journal of Educational Psychology, ISSN 0022-0663, E-ISSN 1939-2176, Vol. 108, no 7, p. 969-981Article in journal (Refereed)
    Abstract [en]

    Educational software in the form of games or so called "computer assisted intervention" for young children has become increasingly common receiving a growing interest and support. Currently there are, for instance, more than 1,000 iPad apps tagged for preschool. Thus, it has become increasingly important to empirically investigate whether these kinds of software actually provide educational benefits for such young children. The study presented in the present article investigated whether preschoolers have the cognitive capabilities necessary to benefit from a teachable-agent-based game of which pedagogical benefits have been shown for older children. The role of executive functions in children's attention was explored by letting 36 preschoolers (3;9-6;3 years) play a teachable-agent-based educational game and measure their capabilities to maintain focus on pedagogically relevant screen events in the presence of competing visual stimuli. Even though the participants did not succeed very well in an inhibition pretest, results showed that they nonetheless managed to inhibit distractions during game-play. It is suggested that the game context acts as a motivator that scaffolds more mature cognitive capabilities in young children than they exhibit during a noncontextual standardized test. The results further indicate gender differences in the development of these capabilities.

  • 61.
    Ayyalasomayajula, Kalyan Ram
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Learning based segmentation and generation methods for handwritten document images2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Computerized analysis of handwritten documents is an active research area in image analysis and computer vision. The goal is to create tools that can be available for use at university libraries and for researchers in the humanities. Working with large collections of handwritten documents is very time consuming and many old books and letters remain unread for centuries. Efficient computerized methods could help researchers in history, philology and computer linguistics to cost-effectively conduct a whole new type of research based on large collections of documents. The thesis makes a contribution to this area through the development of methods based on machine learning. The passage of time degrades historical documents. Humidity, stains, heat, mold and natural aging of the materials for hundreds of years make the documents increasingly difficult to interpret. The first half of the dissertation is therefore focused on cleaning the visual information in these documents by image segmentation methods based on energy minimization and machine learning. However, machine learning algorithms learn by imitating what is expected of them. One prerequisite for these methods to work is that ground truth is available. This causes a problem for historical documents because there is a shortage of experts who can help to interpret and interpret them. The second part of the thesis is therefore about automatically creating synthetic documents that are similar to handwritten historical documents. Because they are generated from a known text, they have a given facet. The visual content of the generated historical documents includes variation in the writing style and also imitates degradation factors to make the images realistic. When machine learning is trained on synthetic images of handwritten text, with a known facet, in many cases they can even give an even better result for real historical documents.

    List of papers
    1. Document binarization using topological clustering guided Laplacian Energy Segmentation
    Open this publication in new window or tab >>Document binarization using topological clustering guided Laplacian Energy Segmentation
    2014 (English)In: Proceedings International Conference on Frontiers in Handwriting Recognition (ICFHR), 2014, 2014, p. 523-528Conference paper, Published paper (Refereed)
    Abstract [en]

    The current approach for text binarization proposesa clustering algorithm as a preprocessing stage toan energy-based segmentation method. It uses a clusteringalgorithm to obtain a coarse estimate of the background (BG)and foreground (FG) pixels. These estimates are used as a priorfor the source and sink points of a graph cut implementation,which is used to efficiently find the minimum energy solution ofan objective function to separate the BG and FG. The binaryimage thus obtained is used to refine the edge map that guidesthe graph cut algorithm. A final binary image is obtained byonce again performing the graph cut guided by the refinededges on a Laplacian of the image.

    Series
    Frontiers in Handwriting Recognition, ISSN 2167-6445 ; 14
    Keywords
    Image Processing; Classification; Machine Learning; Graph-theoretic methods.
    National Category
    Computer Systems Signal Processing
    Research subject
    Computer Science
    Identifiers
    urn:nbn:se:uu:diva-238316 (URN)10.1109/ICFHR.2014.94 (DOI)978-1-4799-4335-7 (ISBN)
    Conference
    International Conference on Frontiers in Handwriting Recognition (ICFHR),September 1-4, 2014, Crete, Greece.
    Funder
    Swedish Research Council, 2012-5743
    Available from: 2014-12-11 Created: 2014-12-11 Last updated: 2019-03-19Bibliographically approved
    2. Historical document binarization combining semantic labeling and graph cuts
    Open this publication in new window or tab >>Historical document binarization combining semantic labeling and graph cuts
    2017 (English)In: Image Analysis: Part I, Springer, 2017, p. 386-396Conference paper, Published paper (Refereed)
    Abstract [en]

    Most data mining applications on collections of historical documents require binarization of the digitized images as a pre-processing step. Historical documents are often subjected to degradations such as parchment aging, smudges and bleed through from the other side. The text is sometimes printed, but more often handwritten. Mathematical modeling of appearance of the text, background and all kinds of degradations, is challenging. In the current work we try to tackle binarization as pixel classification problem. We first apply semantic segmentation, using fully convolutional neural networks. In order to improve the sharpness of the result, we then apply a graph cut algorithm. The labels from the semantic segmentation are used as approximate estimates of the text and background, with the probability map of background used for pruning the edges in the graph cut. The results obtained show significant improvement over the state of the art approach.

    Place, publisher, year, edition, pages
    Springer, 2017
    Series
    Lecture Notes in Computer Science, ISSN 0302-9743 ; 10269
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-335335 (URN)10.1007/978-3-319-59126-1_32 (DOI)000454359300032 ()978-3-319-59125-4 (ISBN)
    Conference
    SCIA 2017, June 12–14, Tromsø, Norway
    Funder
    Swedish Research Council, 2012-5743Riksbankens Jubileumsfond, NHS14-2068:1
    Available from: 2017-05-19 Created: 2017-12-04 Last updated: 2019-03-19Bibliographically approved
    3. PDNet: Semantic segmentation integrated with a primal-dual network for document binarization
    Open this publication in new window or tab >>PDNet: Semantic segmentation integrated with a primal-dual network for document binarization
    2019 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 121, p. 52-60Article in journal (Refereed) Published
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-366933 (URN)10.1016/j.patrec.2018.05.011 (DOI)000459876700008 ()
    Funder
    Swedish Research Council, 2012-5743Riksbankens Jubileumsfond, NHS14-2068:1
    Available from: 2018-05-16 Created: 2018-11-27 Last updated: 2019-04-04Bibliographically approved
    4. Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models
    Open this publication in new window or tab >>Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models
    2016 (English)In: Advances in Visual Computing: Part I, Springer, 2016, p. 278-287Conference paper, Published paper (Refereed)
    Place, publisher, year, edition, pages
    Springer, 2016
    Series
    Lecture Notes in Computer Science ; 10072
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-308662 (URN)10.1007/978-3-319-50835-1_26 (DOI)978-3-319-50834-4 (ISBN)
    Conference
    ISVC 2016, December 12–14, Las Vegas, NV
    Projects
    q2b – From Quill to Bytes
    Available from: 2016-12-10 Created: 2016-11-29 Last updated: 2019-03-19Bibliographically approved
    5. CalligraphyNet: Augmenting handwriting generation with quill based stroke width
    Open this publication in new window or tab >>CalligraphyNet: Augmenting handwriting generation with quill based stroke width
    2019 (English)Manuscript (preprint) (Other academic)
    Abstract [en]

    Realistic handwritten document generation garners a lot ofinterest from the document research community for its abilityto generate annotated data. In the current approach we haveused GAN-based stroke width enrichment and style transferbased refinement over generated data which result in realisticlooking handwritten document images. The GAN part of dataaugmentation transfers the stroke variation introduced by awriting instrument onto images rendered from trajectories cre-ated by tracking coordinates along the stylus movement. Thecoordinates from stylus movement are augmented with thelearned stroke width variations during the data augmentationblock. An RNN model is then trained to learn the variationalong the movement of the stylus along with the stroke varia-tions corresponding to an input sequence of characters. Thismodel is then used to generate images of words or sentencesgiven an input character string. A document image thus cre-ated is used as a mask to transfer the style variations of the inkand the parchment. The generated image can capture the colorcontent of the ink and parchment useful for creating annotated data.

    National Category
    Computer Systems
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-379633 (URN)
    Conference
    26th IEEE International Conference on Image Processing
    Note

    Currently under review

    Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-04-08
  • 62.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Document Binarization Combining with Graph Cuts and Deep Neural Networks2017Conference paper (Other academic)
  • 63.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Document binarization using topological clustering guided Laplacian Energy Segmentation2014In: Proceedings International Conference on Frontiers in Handwriting Recognition (ICFHR), 2014, 2014, p. 523-528Conference paper (Refereed)
    Abstract [en]

    The current approach for text binarization proposesa clustering algorithm as a preprocessing stage toan energy-based segmentation method. It uses a clusteringalgorithm to obtain a coarse estimate of the background (BG)and foreground (FG) pixels. These estimates are used as a priorfor the source and sink points of a graph cut implementation,which is used to efficiently find the minimum energy solution ofan objective function to separate the BG and FG. The binaryimage thus obtained is used to refine the edge map that guidesthe graph cut algorithm. A final binary image is obtained byonce again performing the graph cut guided by the refinededges on a Laplacian of the image.

  • 64.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Historical document binarization combining semantic labeling and graph cuts2017In: Image Analysis: Part I, Springer, 2017, p. 386-396Conference paper (Refereed)
    Abstract [en]

    Most data mining applications on collections of historical documents require binarization of the digitized images as a pre-processing step. Historical documents are often subjected to degradations such as parchment aging, smudges and bleed through from the other side. The text is sometimes printed, but more often handwritten. Mathematical modeling of appearance of the text, background and all kinds of degradations, is challenging. In the current work we try to tackle binarization as pixel classification problem. We first apply semantic segmentation, using fully convolutional neural networks. In order to improve the sharpness of the result, we then apply a graph cut algorithm. The labels from the semantic segmentation are used as approximate estimates of the text and background, with the probability map of background used for pruning the edges in the graph cut. The results obtained show significant improvement over the state of the art approach.

  • 65.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Semantic Labeling using Convolutional Networks coupled with Graph-Cuts for Document binarization2017Conference paper (Other academic)
  • 66.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Topological clustering guided document binarization2015Report (Other academic)
    Abstract [en]

    The current approach for text binarization proposes a clustering algorithm as a preprocessing stage to an energy-based segmentation method. It uses a clustering algorithm to obtain a coarse estimate of the background (BG) and foreground (FG) pixels. These estimates are usedas a prior for the source and sink points of a graph cut implementation, which is used to efficiently find the minimum energy solution of an objective function to separate the BG and FG. The binary image thus obtained is used to refine the edge map that guides the graph cut algorithm. A final binary image is obtained by once again performing the graph cut guided by the refined edges on Laplacian of the image.

  • 67.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    PDNet: Semantic segmentation integrated with a primal-dual network for document binarization2019In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 121, p. 52-60Article in journal (Refereed)
    The full text will be freely available from 2020-05-17 16:13
  • 68.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Nettelblad, Carl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models2016In: Advances in Visual Computing: Part I, Springer, 2016, p. 278-287Conference paper (Refereed)
  • 69.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Wilkinson, Tomas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    CalligraphyNet: Augmenting handwriting generation with quill based stroke width2019Manuscript (preprint) (Other academic)
    Abstract [en]

    Realistic handwritten document generation garners a lot ofinterest from the document research community for its abilityto generate annotated data. In the current approach we haveused GAN-based stroke width enrichment and style transferbased refinement over generated data which result in realisticlooking handwritten document images. The GAN part of dataaugmentation transfers the stroke variation introduced by awriting instrument onto images rendered from trajectories cre-ated by tracking coordinates along the stylus movement. Thecoordinates from stylus movement are augmented with thelearned stroke width variations during the data augmentationblock. An RNN model is then trained to learn the variationalong the movement of the stylus along with the stroke varia-tions corresponding to an input sequence of characters. Thismodel is then used to generate images of words or sentencesgiven an input character string. A document image thus cre-ated is used as a mask to transfer the style variations of the inkand the parchment. The generated image can capture the colorcontent of the ink and parchment useful for creating annotated data.

  • 70.
    Azar, Jimmy
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Automated Tissue Image Analysis Using Pattern Recognition2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Automated tissue image analysis aims to develop algorithms for a variety of histological applications. This has important implications in the diagnostic grading of cancer such as in breast and prostate tissue, as well as in the quantification of prognostic and predictive biomarkers that may help assess the risk of recurrence and the responsiveness of tumors to endocrine therapy.

    In this thesis, we use pattern recognition and image analysis techniques to solve several problems relating to histopathology and immunohistochemistry applications. In particular, we present a new method for the detection and localization of tissue microarray cores in an automated manner and compare it against conventional approaches.

    We also present an unsupervised method for color decomposition based on modeling the image formation process while taking into account acquisition noise. The method is unsupervised and is able to overcome the limitation of specifying absorption spectra for the stains that require separation. This is done by estimating reference colors through fitting a Gaussian mixture model trained using expectation-maximization.

    Another important factor in histopathology is the choice of stain, though it often goes unnoticed. Stain color combinations determine the extent of overlap between chromaticity clusters in color space, and this intrinsic overlap sets a main limitation on the performance of classification methods, regardless of their nature or complexity. In this thesis, we present a framework for optimizing the selection of histological stains in a manner that is aligned with the final objective of automation, rather than visual analysis.

    Immunohistochemistry can facilitate the quantification of biomarkers such as estrogen, progesterone, and the human epidermal growth factor 2 receptors, in addition to Ki-67 proteins that are associated with cell growth and proliferation. As an application, we propose a method for the identification of paired antibodies based on correlating probability maps of immunostaining patterns across adjacent tissue sections.

    Finally, we present a new feature descriptor for characterizing glandular structure and tissue architecture, which form an important component of Gleason and tubule-based Elston grading. The method is based on defining shape-preserving, neighborhood annuli around lumen regions and gathering quantitative and spatial data concerning the various tissue-types.

    List of papers
    1. Microarray Core Detection by Geometric Restoration
    Open this publication in new window or tab >>Microarray Core Detection by Geometric Restoration
    2012 (English)In: Analytical Cellular Pathology, ISSN 0921-8912, E-ISSN 1878-3651, Vol. 35, no 5-6, p. 381-393Article in journal (Refereed) Published
    Abstract [en]

    Whole-slide imaging of tissue microarrays (TMAs) holds the promise of automated image analysis of a large number of histopathological samples from a single slide. This demands high-throughput image processing to enable analysis of these tissue samples for diagnosis of cancer and other conditions. In this paper, we present a completely automated method for the accurate detection and localization of tissue cores that is based on geometric restoration of the core shapes without placing any assumptions on grid geometry. The method relies on hierarchical clustering in conjunction with the Davies-Bouldin index for cluster validation in order to estimate the number of cores in the image wherefrom we estimate the core radius and refine this estimate using morphological granulometry. The final stage of the algorithm reconstructs circular discs from core sections such that these discs cover the entire region of each core regardless of the precise shape of the core. The results show that the proposed method is able to reconstruct core locations without any evidence of localization error. Furthermore, the algorithm is more efficient than existing methods based on the Hough transform for circle detection. The algorithm's simplicity, accuracy, and computational efficiency allow for automated high-throughput analysis of microarray images.

    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-183618 (URN)10.3233/ACP-2012-0067 (DOI)000311675800005 ()22684152 (PubMedID)
    Available from: 2012-10-30 Created: 2012-10-30 Last updated: 2017-12-07Bibliographically approved
    2. Blind Color Decomposition of Histological Images
    Open this publication in new window or tab >>Blind Color Decomposition of Histological Images
    Show others...
    2013 (English)In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 32, no 6, p. 983-994Article in journal (Refereed) Published
    Abstract [en]

    Cancer diagnosis is based on visual examination under a microscope of tissue sections from biopsies. But whereas pathologists rely on tissue stains to identify morphological features, automated tissue recognition using color is fraught with problems that stem from image intensity variations due to variations in tissue preparation, variations in spectral signatures of the stained tissue, spectral overlap and spatial aliasing in acquisition, and noise at image acquisition. We present a blind method for color decomposition of histological images. The method decouples intensity from color information and bases the decomposition only on the tissue absorption characteristics of each stain. By modeling the charge-coupled device sensor noise, we improve the method accuracy. We extend current linear decomposition methods to include stained tissues where one spectral signature cannot be separated from all combinations of the other tissues' spectral signatures. We demonstrate both qualitatively and quantitatively that our method results in more accurate decompositions than methods based on non-negative matrix factorization and independent component analysis. The result is one density map for each stained tissue type that classifies portions of pixels into the correct stained tissue allowing accurate identification of morphological features that may be linked to cancer.

    National Category
    Medical Image Processing
    Research subject
    Computerized Image Processing
    Identifiers
    urn:nbn:se:uu:diva-160312 (URN)10.1109/TMI.2013.2239655 (DOI)000319701800002 ()
    Available from: 2011-10-21 Created: 2011-10-21 Last updated: 2018-12-02
    3. Histological Stain Evaluation for Machine Learning Applications
    Open this publication in new window or tab >>Histological Stain Evaluation for Machine Learning Applications
    2012 (English)In: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention, 2012Conference paper, Published paper (Refereed)
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-183619 (URN)
    Conference
    MICCAI 2012, the 15th International Conference on Medical Image Computing and Computer Assisted Intervention, October 1-5, 2012, Nice, France
    Available from: 2012-10-30 Created: 2012-10-30 Last updated: 2015-01-23
    4. Image segmentation and identification of paired antibodies in breast tissue
    Open this publication in new window or tab >>Image segmentation and identification of paired antibodies in breast tissue
    2014 (English)In: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, p. 647273:1-11Article in journal (Refereed) Published
    Abstract [en]

    Comparing staining patterns of paired antibodies designed towards a specific protein but toward different epitopes of the protein provides quality control over the binding and the antibodies' ability to identify the target protein correctly and exclusively. We present a method for automated quantification of immunostaining patterns for antibodies in breast tissue using the Human Protein Atlas database. In such tissue, dark brown dye 3,3'-diaminobenzidine is used as an antibody-specific stain whereas the blue dye hematoxylin is used as a counterstain. The proposed method is based on clustering and relative scaling of features following principal component analysis. Our method is able (1) to accurately segment and identify staining patterns and quantify the amount of staining and (2) to detect paired antibodies by correlating the segmentation results among different cases. Moreover, the method is simple, operating in a low-dimensional feature space, and computationally efficient which makes it suitable for high-throughput processing of tissue microarrays.

    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-229978 (URN)10.1155/2014/647273 (DOI)000338856800001 ()25061472 (PubMedID)
    Projects
    eSSENCE
    Available from: 2014-07-01 Created: 2014-08-18 Last updated: 2017-12-05Bibliographically approved
    5. Automated Classification of Glandular Tissue by Statistical Proximity Sampling
    Open this publication in new window or tab >>Automated Classification of Glandular Tissue by Statistical Proximity Sampling
    2015 (English)In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, article id 943104Article in journal (Refereed) Published
    Abstract [en]

    Due to the complexity of biological tissue and variations in staining procedures, features that are based on the explicit extraction of properties from subglandular structures in tissue images may have difficulty generalizing well over an unrestricted set of images and staining variations. We circumvent this problem by an implicit representation that is both robust and highly descriptive, especially when combined with a multiple instance learning approach to image classification. The new feature method is able to describe tissue architecture based on glandular structure. It is based on statistically representing the relative distribution of tissue components around lumen regions, while preserving spatial and quantitative information, as a basis for diagnosing and analyzing different areas within an image. We demonstrate the efficacy of the method in extracting discriminative features for obtaining high classification rates for tubular formation in both healthy and cancerous tissue, which is an important component in Gleason and tubule-based Elston grading. The proposed method may be used for glandular classification, also in other tissue types, in addition to general applicability as a region-based feature descriptor in image analysis where the image represents a bag with a certain label (or grade) and the region-based feature vectors represent instances.

    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-230871 (URN)10.1155/2015/943104 (DOI)000362067400001 ()
    Available from: 2014-09-01 Created: 2014-09-01 Last updated: 2017-12-05Bibliographically approved
  • 71.
    Azar, Jimmy C.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Simonsson, Martin
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Image segmentation and identification of paired antibodies in breast tissue2014In: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, p. 647273:1-11Article in journal (Refereed)
    Abstract [en]

    Comparing staining patterns of paired antibodies designed towards a specific protein but toward different epitopes of the protein provides quality control over the binding and the antibodies' ability to identify the target protein correctly and exclusively. We present a method for automated quantification of immunostaining patterns for antibodies in breast tissue using the Human Protein Atlas database. In such tissue, dark brown dye 3,3'-diaminobenzidine is used as an antibody-specific stain whereas the blue dye hematoxylin is used as a counterstain. The proposed method is based on clustering and relative scaling of features following principal component analysis. Our method is able (1) to accurately segment and identify staining patterns and quantify the amount of staining and (2) to detect paired antibodies by correlating the segmentation results among different cases. Moreover, the method is simple, operating in a low-dimensional feature space, and computationally efficient which makes it suitable for high-throughput processing of tissue microarrays.

  • 72.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Natasa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Single image super-resolution reconstruction in presence of mixed Poisson-Gaussian noise2016In: 2016 SIXTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA), IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    Single image super-resolution (SR) reconstructionaims to estimate a noise-free and blur-free high resolution imagefrom a single blurred and noisy lower resolution observation.Most existing SR reconstruction methods assume that noise in theimage is white Gaussian. Noise resulting from photon countingdevices, as commonly used in image acquisition, is, however,better modelled with a mixed Poisson-Gaussian distribution. Inthis study we propose a single image SR reconstruction methodbased on energy minimization for images degraded by mixedPoisson-Gaussian noise.We evaluate performance of the proposedmethod on synthetic images, for different levels of blur andnoise, and compare it with recent methods for non-Gaussiannoise. Analysis shows that the appropriate treatment of signaldependentnoise, provided by our proposed method, leads tosignificant improvement in reconstruction performance.

  • 73.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sladoje, Nataša
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Blind restoration of images degraded with mixed poisson-Gaussian noise with application in transmission electron microscopy2016In: 2016 Ieee 13Th International Symposium On Biomedical Imaging (ISBI), IEEE, 2016, p. 123-127Conference paper (Refereed)
    Abstract [en]

    Noise and blur, present in images after acquisition, negatively affect their further analysis. For image enhancement when the Point Spread Function (PSF) is unknown, blind deblurring is suitable, where both the PSF and the original image are simultaneously reconstructed. In many realistic imaging conditions, noise is modelled as a mixture of Poisson (signal-dependent) and Gaussian (signal independent) noise. In this paper we propose a blind deconvolution method for images degraded by such mixed noise. The method is based on regularized energy minimization. We evaluate its performance on synthetic images, for different blur kernels and different levels of noise, and compare with non-blind restoration. We illustrate the performance of the method on Transmission Electron Microscopy images of cilia, used in clinical practice for diagnosis of a particular type of genetic disorders.

  • 74.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Nataša
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Restoration of images degraded by signal-dependent noise based on energy minimization: an empirical study2016In: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 25, no 4, article id 043020Article in journal (Refereed)
    Abstract [en]

    Most energy minimization-based restoration methods are developed for signal-independent Gaussian noise. The assumption of Gaussian noise distribution leads to a quadratic data fidelity term, which is appealing in optimization. When an image is acquired with a photon counting device, it contains signal-dependent Poisson or mixed Poisson–Gaussian noise. We quantify the loss in performance that occurs when a restoration method suited for Gaussian noise is utilized for mixed noise. Signal-dependent noise can be treated by methods based on either classical maximum a posteriori (MAP) probability approach or on a variance stabilization approach (VST). We compare performances of these approaches on a large image material and observe that VST-based methods outperform those based on MAP in both quality of restoration and in computational efficiency. We quantify improvement achieved by utilizing Huber regularization instead of classical total variation regularization. The conclusion from our study is a recommendation to utilize a VST-based approach combined with regularization by Huber potential for restoration of images degraded by blur and signal-dependent noise. This combination provides a robust and flexible method with good performance and high speed.

  • 75. Bajic, Buda
    et al.
    Suveer, Amit
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Gupta, Anindya
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Pepic, Ivana
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sladoje, Natasa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Denoising of short exposure transmission electron microscopy images for ultrastructural enhancement2018In: Proc. 15th International Symposium on Biomedical Imaging, IEEE, 2018, p. 921-925Conference paper (Refereed)
  • 76. Bajić, Buda
    et al.
    Lindblad, Joakim
    Sladoje, Nataša
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An evaluation of potential functions for regularized image deblurring2014In: Image Analysis and Recognition: Part I, Springer Berlin/Heidelberg, 2014, p. 150-158Conference paper (Refereed)
  • 77.
    Barrera, Tony
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    A chronological and mathematical overview of digital circle generation algorithms: Introducing efficient 4- and 8-connected circles2016In: International Journal of Computer Mathematics, ISSN 0020-7160, E-ISSN 1029-0265, Vol. 93, no 8, p. 1241-1253Article in journal (Refereed)
    Abstract [en]

    Circles are one of the basic drawing primitives for computers and while the naive way of setting up an equation for drawing circles is simple, implementing it in an efficient way using integer arithmetic has resulted in quite a few different algorithms. We present a short chronological overview of the most important publications of such digital circle generation algorithms. Bresenham is often assumed to have invented the first all integer circle algorithm. However, there were other algorithms published before his first official publication, which did not use floating point operations. Furthermore, we present both a 4- and an 8-connected all integer algorithm. Both of them proceed without any multiplication, using just one addition per iteration to compute the decision variable, which makes them more efficient than previously published algorithms.

  • 78. Barrera, Tony
    et al.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    An Algorithm for Parallel Calculation of Trigonometric and Exponential Functions2013In: ACM International Conference on Computing Frontiers, 2013Conference paper (Refereed)
  • 79. Beltrán-Castañón, César
    et al.
    Nyström, IngelaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.Famili, Fazel
    Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications2017Conference proceedings (editor) (Refereed)
  • 80.
    Benedek, Nagy
    et al.
    University of Debrecen, Department of Computer Science, Debrecen Hungary .
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Normand, Nicolas
    Universit ́ de Nantes, IRCCyN UMR CNRS 6597, Nantes, France.
    A Weight Sequence Distance Function2013In: : Mathematical Morphology and Its Applications to Signal and Image Processing / [ed] Cris L. Luengo Hendriks, Gunilla Borgefors, Robin Strand, Springer Berlin/Heidelberg, 2013, p. 292-301Conference paper (Refereed)
    Abstract [en]

    In this paper, a family of weighted neighborhood sequence distance functions defined on the square grid is presented. With this distance function, the allowed weight between any two adjacent pixels along a path is given by a weight sequence. We build on our previous results, where only two or three unique weights are considered, and present a framework that allows any number of weights. We show that the rotational dependency can be very low when as few as three or four unique weights are used. An algorithm for computing the distance transform (DT) that can be used for image processing applications is also presented.

  • 81.
    Bengtsson Bernander, Karl
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    A Method for Detecting Resident Space Objects and Orbit Determination Based on Star Trackers and Image Analysis2014Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Satellites commonly use onboard digital cameras, called star trackers. A star tracker determines the satellite's attitude, i.e. its orientation in space, by comparing star positions with databases of star patterns. In this thesis, I investigate the possibility of extending the functionality of star trackers to also detect the presence of resident space objects (RSO) orbiting the earth. RSO consist of both active satellites and orbital debris, such as inactive satellites, spent rocket stages and particles of different sizes.

    I implement and compare nine detection algorithms based on image analysis. The input is two hundred synthetic images, consisting of a portion of the night sky with added random Gaussian and banding noise. RSO, visible as faint lines in random positions, are added to half of the images. The algorithms are evaluated with respect to sensitivity (the true positive rate) and specificity (the true negative rate). Also, a difficulty metric encompassing execution times and computational complexity is used.

    The Laplacian of Gaussian algorithm outperforms the rest, with a sensitivity of 0.99, a specificity of 1 and a low difficulty. It is further tested to determine how its performance changes when varying parameters such as line length and noise strength. For high sensitivity, there is a lower limit in how faint the line can appear.

    Finally, I show that it is possible to use the extracted information to roughly estimate the orbit of the RSO. This can be accomplished using the Gaussian angles-only method. Three angular measurements of the RSO positions are needed, in addition to the times and the positions of the observer satellite. A computer architecture capable of image processing is needed for an onboard implementation of the method.

  • 82.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Image processing and its hardware support: Analysis vs synthesis - historical trends2017In: Image Analysis, SCIA 2017, Pt I / [ed] P Sharma, F M Bianchi, Switzerland, 2017, p. 3-14Conference paper (Refereed)
    Abstract [en]

    Computers can be used to handle images in two fundamen-tally dierent ways. They can be used to analyse images to obtain quan-titative data or some image understanding. And they can be used tocreate images that can be displayed through computer graphics and vi-sualization. For both of these purposes it is of interest to develop ecientways of representing, compressing and storing the images. While SCIA,the Scandinavia Conference of Image Analysis, according to its name ismainly concerned with the former aspect of images, it is interesting tonote that image analysis throughout its history has been strongly in u-enced also by developments on the visualization side. When the confer-ence series now has reached its 20th milestone it may be worth re ectingon what factors have been important in forming the development of theeld. To understand where you are it is good to know where you comefrom and it may even help you understand where you are going.

  • 83.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Quantitative and automated microscopy: Where do we stand after 80 years of research?2014In: Proc. 11th International Symposium on Biomedical Imaging, Piscataway, NJ: IEEE Press, 2014, p. 274-277Conference paper (Refereed)
  • 84.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Danielsen, Håvard
    Treanor, Darren
    Gurcan, Metin N.
    MacAulay, Calum
    Molnár, Béla
    Computer-aided diagnostics in digital pathology2017In: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 91, no 6, p. 551-554Article in journal (Other academic)
  • 85.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Malm, Patrik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Screening for Cervical Cancer Using Automated Analysis of PAP-Smears2014In: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, Vol. 2014, p. 842037:1-12Article, review/survey (Refereed)
    Abstract [en]

    Cervical cancer is one of the most deadly and common forms of cancer among women if no action is taken to prevent it, yet it is preventable through a simple screening test, the so-called PAP-smear. This is the most effective cancer prevention measure developed so far. But the visual examination of the smears is time consuming and expensive and there have been numerous attempts at automating the analysis ever since the test was introduced more than 60 years ago. The first commercial systems for automated analysis of the cell samples appeared around the turn of the millennium but they have had limited impact on the screening costs. In this paper we examine the key issues that need to be addressed when an automated analysis system is developed and discuss how these challenges have been met over the years. The lessons learned may be useful in the efforts to create a cost-effective screening system that could make affordable screening for cervical cancer available for all women globally, thus preventing most of the quarter million annual unnecessary deaths still caused by this disease.

  • 86.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Tárnok, Attila
    Special Section on Image Cytometry2019In: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 95A, no 4, p. 363-365Article in journal (Other academic)
  • 87.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Uppsala university.
    Wieslander, Håkan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Forslid, Gustav
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Hirsch, Jan-Michael
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Oral and Maxillofacial Surgery.
    Runow Stark, Christina
    Kecheril Sadanandan, Sajith
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Detection of Malignancy-Associated Changes Due to Precancerous and Oral Cancer Lesions: A Pilot Study Using Deep Learning2018In: CYTO2018 / [ed] Andrea Cossarizza, 2018Conference paper (Refereed)
    Abstract [en]

    Background: The incidence of oral cancer is increasing and it is effecting younger individuals. PAP smear-based screening, visual, and automated, have been used for decades, to successfully decrease the incidence of cervical cancer. Can similar methods be used for oral cancer screening? We have carried out a pilot study using neural networks for classifying cells, both from cervical cancer and oral cancer patients. The results which were reported from a technical point of view at the 2017 IEEE International Conference on Computer Vision Workshop (ICCVW), were particularly interesting for the oral cancer cases, and we are currently collecting and analyzing samples from more patients. Methods: Samples were collected with a brush in the oral cavity and smeared on glass slides, stained, and prepared, according to standard PAP procedures. Images from the slides were digitized with a 0.35 micron pixel size, using focus stacks with 15 levels 0.4 micron apart. Between 245 and 2,123 cell nuclei were manually selected for analysis for each of 14 datasets, usually 2 datasets for each of the 6 cases, in total around 15,000 cells. A small region was cropped around each nucleus, and the best 2 adjacent focus layers in each direction were automatically found, thus creating images of 100x100x5 pixels. Nuclei were chosen with an aim to select well preserved free-lying cells, with no effort to specifically select diagnostic cells. We therefore had no ground truth on the cellular level, only on the patient level. Subsets of these images were used for training 2 sets of neural networks, created according to the ResNet and VGG architectures described in literature, to distinguish between cells from healthy persons, and those with precancerous lesions. The datasets were augmented through mirroring and 90 degrees rotations. The resulting networks were used to classify subsets of cells from different persons, than those in the training sets. This was repeated for a total of 5 folds. Results: The results were expressed as the percentage of cell nuclei that the neural networks indicated as positive. The percentage of positive cells from healthy persons was in the range 8% to 38%. The percentage of positive cells collected near the lesions was in the range 31% to 96%. The percentages from the healthy side of the oral cavity of patients with lesions ranged 37% to 89%. For each fold, it was possible to find a threshold for the number of positive cells that would correctly classify all patients as normal or positive, even for the samples taken from the healthy side of the oral cavity. The network based on the ResNet architecture showed slightly better performance than the VGG-based one. Conclusion: Our small pilot study indicates that malignancyassociated changes that can be detected by neural networks may exist among cells in the oral cavity of patients with precancerous lesions. We are currently collecting samples from more patients, and will present those results as well, with our poster at CYTO 2018.

  • 88. Bernander, Karl B.
    et al.
    Gustavsson, Kenneth
    Selig, Bettina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Improving the stochastic watershed2013In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, no 9, p. 993-1000Article in journal (Refereed)
    Abstract [en]

    The stochastic watershed is an unsupervised segmentation tool recently proposed by Angulo and Jeulin. By repeated application of the seeded watershed with randomly placed markers, a probability density function for object boundaries is created. In a second step, the algorithm then generates a meaningful segmentation of the image using this probability density function. The method performs best when the image contains regions of similar size, since it tends to break up larger regions and merge smaller ones. We propose two simple modifications that greatly improve the properties of the stochastic watershed: (1) add noise to the input image at every iteration, and (2) distribute the markers using a randomly placed grid. The noise strength is a new parameter to be set, but the output of the algorithm is not very sensitive to this value. In return, the output becomes less sensitive to the two parameters of the standard algorithm. The improved algorithm does not break up larger regions, effectively making the algorithm useful for a larger class of segmentation problems.

  • 89.
    Bertilsson, Axel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Samuelsson, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Användarcentrerad utvecklingav digitalt verktyg för ökad motivation till fysisk aktivitet2019Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This study aims to provide hypotheses regarding how a digital application can help individuals and professionals in the health industry to facilitate and promote physical activity through increased motivation. The study includes interviews with professionals in the health industry and self-determination theory as the basis for the development of the application. The result is presented through a final test where the application is used at a gym and a corresponding test where test persons instead use a paper-based tool. Users were then asked to fill out surveys to measure motivation. The result shows that an improvement is possible with the help of digitization of the paper method. It also shows that this needs to be further investigated in new studies before the hypotheses can be proved. Based on this result, two hypotheses are formulated for future studies.

    - A digital application with anchoring in self-determination theory that focuses on promoting autonomy, competence and relatedness is more motivating than paper- based tools.- A digital application created from existing evidence-based tools increases motivation compared to paper-based solutions.

  • 90. Bhatt, Manish
    et al.
    Ayyalasomayajula, Kalyan R.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Yalavarthy, Phaneendra K.
    Generalized Beer–Lambert model for near-infrared light propagation in thick biological tissues2016In: Journal of Biomedical Optics, ISSN 1083-3668, E-ISSN 1560-2281, Vol. 21, no 7, article id 076012Article in journal (Refereed)
  • 91.
    Bianchi, Kevin
    et al.
    ISIT UMR6284 CNRS, Univ. d’Auvergne BP10448, F-63000 Clermont-Ferrand.
    Vacavant, Antoine
    ISIT UMR6284 CNRS, Univ. d’Auvergne BP10448, F-63000 Clermont-Ferrand.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Terve, Pierre
    KEOSYS Company 1, impasse Auguste Fresnel, F 44815 Saint Herblain.
    Sarry, Laurent
    ISIT UMR6284 CNRS, Univ. d’Auvergne BP10448, F-63000 Clermont-Ferrand.
    Dual B-spline Snake for Interactive Myocardial Segmentation2013Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel interactive segmentation formalism based on two coupledB-Spline snake models to efficiently and simultaneously extract myocardial walls fromshort-axis magnetic resonance images. The main added value of this model is interactionas it is possible to quickly and intuitively correct the result in complex cases withoutrestarting the whole segmentation working flow. During this process, energies computedfrom the images guide the user to the best position of the model.

  • 92. Björk, Ingrid
    et al.
    Kavathatzopoulos, Iordanis
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Language and teaching ethics2018Conference paper (Refereed)
    Abstract [en]

    All problems with learning are increased when using English to teach non-English native students because of the culturally-sensitive nature of the subject of ethics. Coming to teaching ethics we are confronted with more difficulties. What is right and wrong is often affected by the culture, and different cultures often have different languages. Ethics theories are also expressed in language terms and they can be more easily misunderstood or misinterpreted compared to natural science theories. The feelings and every-day life encounters with “right” and “wrong” are linguistically experienced, described, and mediated. Therefore, language has a strong impact on whether something is ethical or whether it makes sense as an ethical issue at all.

  • 93.
    Björk, Ingrid
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Kavathatzopoulos, Iordanis
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Robots, ethics and language2015In: Computers & Society: The Newsletter of the ACM Special Interest Group on Computers and Society Special Issue on 20 Years of ETHICOMP / [ed] Mark Coeckelbergh, Bernd Stahl, and Catherine Flick; Vaibhav Garg and Dee Weikle, ACM Digital Library, 2015, p. 268-273Conference paper (Refereed)
    Abstract [en]

    Following the classical philosophical definition of ethics and the psychological research on problem solving and decision making, the issue of ethics becomes concrete and opens up the way for the creation of IT systems that can support handling of moral problems. Also in a sense that is similar to the way humans handle their moral problems. The processes of communicating information and receiving instructions are linguistic by nature. Moreover, autonomous and heteronomous ethical thinking is expressed by way of language use. Indeed, the way we think ethically is not only linguistically mediated but linguistically construed – whether we think for example in terms of conviction and certainty (meaning heteronomy) or in terms of questioning and inquiry (meaning autonomy). A thorough analysis of the language that is used in these processes is therefore of vital importance for the development of the above mentioned tools and methods. Given that we have a clear definition based on philosophical theories and on research on human decision-making and linguistics, we can create and apply systems that can handle ethical issues. Such systems will help us to design robots and to prescribe their actions, to communicate and cooperate with them, to control the moral aspects of robots’ actions in real life applications, and to create embedded systems that allow continuous learning and adaptation.

  • 94.
    Blache, Ludovic
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
    Nysjö, Fredrik
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Thor, Andreas
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Plastic Surgery.
    Rodriguez-Lorenzo, Andres
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Plastic Surgery.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    SoftCut:: A Virtual Planning Tool for Soft Tissue Resection on CT Images2018In: Medical Image Understanding and Analysis / [ed] Mark Nixon; Sasan Mahmoodi; Reyer Zwiggelaar, Cham: Springer, 2018, Vol. 894, p. 299-310Conference paper (Refereed)
    Abstract [en]

    With the increasing use of three-dimensional (3D) models and Computer Aided Design (CAD) in the medical domain, virtual surgical planning is now frequently used. Most of the current solutions focus on bone surgical operations. However, for head and neck oncologic resection, soft tissue ablation and reconstruction are common operations. In this paper, we propose a method to provide a fast and efficient estimation of shape and dimensions of soft tissue resections. Our approach takes advantage of a simple sketch-based interface which allows the user to paint the contour of the resection on a patient specific 3D model reconstructed from a computed tomography (CT) scan. The volume is then virtually cut and carved following this pattern. From the outline of the resection defined on the skin surface as a closed curve, we can identify which areas of the skin are inside or outside this shape. We then use distance transforms to identify the soft tissue voxels which are closer from the inside of this shape. Thus, we can propagate the shape of the resection inside the soft tissue layers of the volume. We demonstrate the usefulness of the method on patient specific CT data.

  • 95.
    Bodin, Ida
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Cognitive work analysis in practice: Adaptation to project scope and industrial context2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The Cognitive Work Analysis (CWA) framework is widely used by researchers for the analysis of complex systems. It, however, lacks the same impact amongst industrial practitioners. This thesis investigates possible adaptations of the framework to project and industrial constraints, and the consequences associated with such adaptations. Long haul heavy vehicle transportation is the application domain for the work presented in the thesis. The CWA framework has been applied within the Methods for Designing Future Autonomous Systems (MODAS) project. Adaptations have been made to fit the framework within the project constraints and the industrial contexts. Interviews with stakeholders in an industrial organization regarding possible use of models from the CWA framework have been made. The CWA was scaled to available resources when applied within the MODAS project. From this we realized that prioritization of work activity can have consequences on the resulting systems ability to handle unforeseen events. Further, a focus on the current system probed a rapid out-dating of the analysis due to technical development. The conclusion is that even if advantages are lost during adaptation due to practical constraints, the CWA framework could add value to practitioners within industry if adapted to the industrial context.

    List of papers
    1. Developing a 1st Iteration Concept HMI for Supervising and Controlling a Self-Driving Truck
    Open this publication in new window or tab >>Developing a 1st Iteration Concept HMI for Supervising and Controlling a Self-Driving Truck
    Show others...
    (English)Manuscript (preprint) (Other academic)
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-335442 (URN)
    Available from: 2017-12-05 Created: 2017-12-05 Last updated: 2018-01-13
    2. Development and Assessment of Concept HMI for Supervising and Controlling a SelfDriving Truck
    Open this publication in new window or tab >>Development and Assessment of Concept HMI for Supervising and Controlling a SelfDriving Truck
    Show others...
    (English)Manuscript (preprint) (Other academic)
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-335451 (URN)
    Note

    Title in thesis list of papers: "Developing and Assessing a 2nd and 3rd Iteration Concept HMI for Supervising and Controlling a Self-Driving Truck"

    Available from: 2017-12-05 Created: 2017-12-05 Last updated: 2018-01-13
    3. Activity prioritization to focus the control task analysis
    Open this publication in new window or tab >>Activity prioritization to focus the control task analysis
    2016 (English)In: Journal of Cognitive Engineering and Decision Making, ISSN 1555-3434, E-ISSN 2169-5032, Vol. 10, no 1, p. 91-104Article in journal (Refereed) Published
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-298003 (URN)10.1177/1555343416629307 (DOI)000374661200006 ()
    Projects
    MODAS
    Available from: 2016-03-01 Created: 2016-06-29 Last updated: 2018-01-13Bibliographically approved
    4. Rebuttal to Burns and Naikar
    Open this publication in new window or tab >>Rebuttal to Burns and Naikar
    2016 (English)In: Journal of Cognitive Engineering and Decision Making, ISSN 1555-3434, E-ISSN 2169-5032, Vol. 10, no 1, p. 109-110Article in journal, Editorial material (Other academic) Published
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-299392 (URN)10.1177/1555343416629179 (DOI)000374661200008 ()
    Available from: 2016-03-31 Created: 2016-07-18 Last updated: 2018-01-10Bibliographically approved
    5. Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    Open this publication in new window or tab >>Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    2018 (English)In: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 19, no 1, p. 101-117Article in journal (Refereed) Published
    Abstract [en]

    Introducing automation in a human-machine system changes the tasks performed by human operators. It is difficult to analyse systems for which there are no experienced operators. This issue emerged within a project with the aim to develop a human–machine interface for a highly automated long-haul vehicle. To handle the problem, a formative strategies analysis method with promises to enable desktop analyses through predefined strategy categories was adopted. The method was used to investigate strategies for controlling the future long haul vehicle by conducting workshops with today's drivers. The method was shown to be a valuable asset in eliciting strategies for revolutionary design.

    Keywords
    Cognitive work analysis, strategies analysis, automation, revolutionary systems design, long haul trucks
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-292799 (URN)10.1080/1463922X.2017.1278805 (DOI)000428728900006 ()
    Projects
    MODAS
    Funder
    VINNOVA, 2012-03678
    Available from: 2017-01-27 Created: 2016-05-09 Last updated: 2019-01-09Bibliographically approved
    6. Supporting industrial uptake of cognitive work analysis
    Open this publication in new window or tab >>Supporting industrial uptake of cognitive work analysis
    2015 (English)In: Proc. Human Factors and Ergonomics Society 59th Annual Meeting, Thousand Oaks, CA: Sage Publications, 2015, p. 170-174Conference paper, Published paper (Refereed)
    Abstract [en]

    As part of a broader industrial project, the first two stages of a Cognitive Work Analysis (CWA, Work Domain Analysis [WDA] and Control Task Analysis [ConTA]) were completed for Long Haul Commercial Road Transport. To support the potential uptake of CWA by different stakeholders within the industrial organization, parts of the ConTA Contextual Activity Template (CAT) were truncated. The goal of the current, exploratory study, was to identify which stakeholders within the industrial organization could benefit from using the WDA or CAT for either their Strategic (Research) or Product (Development) planning, and over what time horizon. We observed differences in the perceived usefulness of the WDA and the CAT between the different stakeholders. Innovative solutions to the issues raised should significantly enhance the industrial use of Cognitive Work Analysis.

    Place, publisher, year, edition, pages
    Thousand Oaks, CA: Sage Publications, 2015
    National Category
    Human Computer Interaction
    Identifiers
    urn:nbn:se:uu:diva-268730 (URN)978-0-945289-47-0 (ISBN)
    Conference
    HFES 2015, October 26–30, Los Angeles, CA
    Available from: 2015-10-30 Created: 2015-12-09 Last updated: 2018-01-10Bibliographically approved
  • 96.
    Bodin, Ida
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Fröjd, Camilla
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences.
    Arweström Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Work domain analysis of an intensive care unit: An Abstraction Hierarchy based on a bed-side approach2016In: Proc. Human Factors and Ergonomics Society Europe Chapter 2015 Annual Conference, 2016Conference paper (Refereed)
    Abstract [en]

    Work in intensive care units requires interaction with several medical devices and interpretation of dynamic information from several sources. The aim of the current study was to gain understanding of the work domain to support the development of a holistic information environment and further analyses of risky situations. A total of 18 hours of bed-side observations at an intensive care unit and interviews with three experienced intensive care unit nurses were conducted in order to receive input data for the modelling of the work domain. The domain was modelled in an abstraction hierarchy, as according to the first phase of the cognitive work analysis framework. The results show that the ultimate purpose of the work carried out in an intensive care unit is keeping patients alive while gaining time for treatment, but also to perform treatment and relieve symptoms. The purpose is represented at the top level of the model, and lower levels include functions as supporting the patients’ vital functions and avoiding secondary complications. With this work domain analysis as a basis, three different design challenges identified can be dealt with systematically.

  • 97.
    Bodin, Ida
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Krupenia, Stas
    Supporting industrial uptake of cognitive work analysis2015In: Proc. Human Factors and Ergonomics Society 59th Annual Meeting, Thousand Oaks, CA: Sage Publications, 2015, p. 170-174Conference paper (Refereed)
    Abstract [en]

    As part of a broader industrial project, the first two stages of a Cognitive Work Analysis (CWA, Work Domain Analysis [WDA] and Control Task Analysis [ConTA]) were completed for Long Haul Commercial Road Transport. To support the potential uptake of CWA by different stakeholders within the industrial organization, parts of the ConTA Contextual Activity Template (CAT) were truncated. The goal of the current, exploratory study, was to identify which stakeholders within the industrial organization could benefit from using the WDA or CAT for either their Strategic (Research) or Product (Development) planning, and over what time horizon. We observed differences in the perceived usefulness of the WDA and the CAT between the different stakeholders. Innovative solutions to the issues raised should significantly enhance the industrial use of Cognitive Work Analysis.

  • 98.
    Bodin, Ida
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Krupenia, Stas S.
    Activity prioritization to focus the control task analysis2016In: Journal of Cognitive Engineering and Decision Making, ISSN 1555-3434, E-ISSN 2169-5032, Vol. 10, no 1, p. 91-104Article in journal (Refereed)
  • 99.
    Bodin, Ida
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Krupenia, Stas S.
    Rebuttal to Burns and Naikar2016In: Journal of Cognitive Engineering and Decision Making, ISSN 1555-3434, E-ISSN 2169-5032, Vol. 10, no 1, p. 109-110Article in journal (Other academic)
  • 100.
    Boman, Hanna
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Utvärdering av innovationsstöd inom eHälsa i Stockholms läns sjukvårdsområde2015Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis investigates how actors within the health care sector work with innovation and development of information technology products, also called eHealth. eHealth services is an expanding area which will play a vital role in tomorrow's health care system. Staffs within health care organizations do have a lot of ideas of how to develop and improve the work process and how to provide better health care.

    The study was performed at Stockholms läns sjukvårdsområde (SLSO) and the purpose of this project is to evaluate the support given by SLSO innovation gateway. Innovation gateway is an approach that has been spread to some of Sweden's county councils, where the aim is to take advantage of the staffs ideas and to develop products and services based on activities that contribute to improving health care. Interviews and observations have been made to understand the innovation environment in Stockholms läns lansting. This gave an understanding for which user-centred aspects that are important to consider when developing eHealth innovations. Aspects like security, usability and availability are essential to consider when creating innovations that create value for patients and employees. The results also showed that staffs need better support from the organization and an understanding and knowledge in information technology, law and project management to be able to manage and develop eHealth innovations. The study has also shown that the client, the project and developers must all be involved in the innovation process and work with the organization to succeed. It requires a reallocation of resources to enable SLSO to provide the demanded support. 

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