uu.seUppsala universitets publikasjoner
Endre søk
Begrens søket
1234567 51 - 100 of 924
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Treff pr side
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
  • Standard (Relevans)
  • Forfatter A-Ø
  • Forfatter Ø-A
  • Tittel A-Ø
  • Tittel Ø-A
  • Type publikasjon A-Ø
  • Type publikasjon Ø-A
  • Eldste først
  • Nyeste først
  • Skapad (Eldste først)
  • Skapad (Nyeste først)
  • Senast uppdaterad (Eldste først)
  • Senast uppdaterad (Nyeste først)
  • Disputationsdatum (tidligste først)
  • Disputationsdatum (siste først)
Merk
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 51. Aslani, Mohammad
    et al.
    Seipel, Stefan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Wiering, Marco
    Continuous residual reinforcement learning for traffic signal control optimization2018Inngår i: Canadian journal of civil engineering (Print), ISSN 0315-1468, E-ISSN 1208-6029, Vol. 45, nr 8, s. 690-702Artikkel i tidsskrift (Fagfellevurdert)
  • 52.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo, Cris
    Flagship Biosci Inc, Westminster, CO USA.
    Thurley, Matthew
    Lulea Univ Technol, Lulea, Sweden.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    A New Approach to Mathematical Morphology on One Dimensional Sampled Signals2016Inngår i: IEEE Proceedings, International Conference on Pattern Recognition (ICPR 2016), Cancun, Mexico, 2016, 2016Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a new approach to approximate continuous-domain mathematical morphology operators. The approach is applicable to irregularly sampled signals. We define a dilation under this new approach, where samples are duplicated and shifted according to the flat, continuous structuring element. We define the erosion by adjunction, and the opening and closing by composition. These new operators will significantly increase precision in image measurements. Experiments show that these operators indeed approximate continuous-domain operators better than the standard operators on sampled one-dimensional signals, and that they may be applied to signals using structuring elements smaller than the distance between samples. We also show that we can apply the operators to scan lines of a two-dimensional image to filter horizontal and vertical linear structures.

  • 53.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Flagship Biosci Inc, Westminster, CO 80021 USA.
    A Faster, Unbiased Path Opening by Upper Skeletonization and Weighted Adjacency Graphs2016Inngår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 25, nr 12, s. 5589-5600Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The path opening is a filter that preserves bright regions in the image in which a path of a certain length L fits. A path is a (not necessarily straight) line defined by a specific adjacency relation. The most efficient implementation known scales as O(min(L, d, Q)N) with the length of the path, L, the maximum possible path length, d, the number of graylevels, Q, and the image size, N. An approximation exists (parsimonious path opening) that has an execution time independent of path length. This is achieved by preselecting paths, and applying 1D openings along these paths. However, the preselected paths can miss important structures, as described by its authors. Here, we propose a different approximation, in which we preselect paths using a grayvalue skeleton. The skeleton follows all ridges in the image, meaning that no important line structures will be missed. An H-minima transform simplifies the image to reduce the number of branches in the skeleton. A graph-based version of the traditional path opening operates only on the pixels in the skeleton, yielding speedups up to one order of magnitude, depending on image size and filter parameters. The edges of the graph are weighted in order to minimize bias. Experiments show that the proposed algorithm scales linearly with image size, and that it is often slightly faster for longer paths than for shorter paths. The algorithm also yields the most accurate results- as compared with a number of path opening variants-when measuring length distributions.

  • 54.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc, Colorado, USA..
    Thurley, Matthew J.
    Luleå tekniska universitet.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.
    Adaptive Mathematical Morphology on Irregularly Sampled Signals in Two DimensionsManuskript (preprint) (Annet vitenskapelig)
  • 55.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc, Colorado, USA..
    Thurley, Matthew J.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.
    Estimating the Gradient for Images with Missing Samples Using Elliptical Structuring ElementsInngår i: Artikkel i tidsskrift (Fagfellevurdert)
  • 56.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Thurley, Matthew J.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Mathematical morphology on irregularly sampled data in one dimension2017Inngår i: Mathematical Morphology - Theory and Applications, ISSN 2353-3390, Vol. 2, nr 1, s. 1-24Artikkel i tidsskrift (Fagfellevurdert)
  • 57.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc., Westminster, USA.
    Thurley, Matthew
    Luleå University of Technology, Luleå, Sweden.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Mathematical Morphology on Irregularly Sampled Signals2017Inngår i: Computer Vision – ACCV 2016 Workshops. ACCV 2016, Springer, 2017, Vol. 10117, s. 506-520Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper introduces a new operator that can be used to approximate continuous-domain mathematical morphology on irregularly sampled surfaces. We define a new way of approximating the continuous domain dilation by duplicating and shifting samples according to a flat continuous structuring element. We show that the proposed algorithm can better approximate continuous dilation, and that dilations may be sampled irregularly to achieve a smaller sampling without greatly compromising the accuracy of the result.

  • 58.
    Asplund, Teo
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Serna, Andrés
    Terra3D.
    Marcotegui, Beatriz
    MINES ParisTech, PSL Research University, CMM - Centre for Mathematical Morphology.
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.
    Luengo Hendriks, Cris L.
    Flagship Biosciences Inc..
    Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes2019Inngår i: International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, 2019Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

  • 59. Astruc, Marine
    et al.
    Malm, Patrik
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Kumar, Rajesh
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Cluster detection and field-of-view quality rating: Applied to automated Pap-smear analysis2013Inngår i: Proc. 2nd International Conference on Pattern Recognition Applications and Methods, SciTePress, 2013, s. 355-364Konferansepaper (Fagfellevurdert)
    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.

  • 60.
    Avenel, Christophe
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Carlbom, Ingrid
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Blur detection and visualization in histological whole slide images2015Inngår i: Proc. 10th International Conference on Mass Data Analysis of Images and Signals, Leipzig, Germany: IBaI , 2015Konferansepaper (Fagfellevurdert)
    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.

  • 61.
    Avenel, Christophe
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Fortin, Pierre
    Gouicem, Mourad
    Zaidi, Samia
    Solving the Table Maker's Dilemma on current SIMD architectures2016Inngår i: Scalable Computing: Practice and Experience, ISSN 1895-1767, E-ISSN 1895-1767, Vol. 17, nr 3, s. 237-250Artikkel i tidsskrift (Fagfellevurdert)
  • 62.
    Avenel, Christophe
    et al.
    CADESS Med AB, Uppsala, Sweden.
    Tolf, Anna
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Klinisk och experimentell patologi.
    Dragomir, Anca
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Klinisk och experimentell patologi.
    Carlbom, Ingrid
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. 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 Pathology2019Inngår i: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 7, artikkel-id 125Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 63.
    Axelsson, Anton
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Context: The abstract term for the concrete2016Licentiatavhandling, med artikler (Annet vitenskapelig)
    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.

    Delarbeid
    1. Scaffolding executive function capabilities via play-&-learn software for preschoolers
    Åpne denne publikasjonen i ny fane eller vindu >>Scaffolding executive function capabilities via play-&-learn software for preschoolers
    2016 (engelsk)Inngår i: Journal of Educational Psychology, ISSN 0022-0663, E-ISSN 1939-2176, Vol. 108, nr 7, s. 969-981Artikkel i tidsskrift (Fagfellevurdert) 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.

    Emneord
    inhibition; attention; teachable agents; eye tracking; learning by teaching
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-275524 (URN)10.1037/edu0000099 (DOI)000385436300005 ()
    Prosjekter
    Cognition, Communication, and Learning (CCL)
    Forskningsfinansiär
    Swedish Research Council, 437-2014-6735
    Tilgjengelig fra: 2016-01-18 Laget: 2016-02-04 Sist oppdatert: 2018-01-10bibliografisk kontrollert
    2. Collegial verbalisation — the value of an independent observer: an ecological approach
    Åpne denne publikasjonen i ny fane eller vindu >>Collegial verbalisation — the value of an independent observer: an ecological approach
    2015 (engelsk)Inngår i: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 16, nr 5, s. 474-494Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-249009 (URN)10.1080/1463922X.2015.1027322 (DOI)
    Tilgjengelig fra: 2015-04-07 Laget: 2015-04-09 Sist oppdatert: 2019-01-09bibliografisk kontrollert
    3. Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    Åpne denne publikasjonen i ny fane eller vindu >>Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    2018 (engelsk)Inngår i: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 19, nr 1, s. 101-117Artikkel i tidsskrift (Fagfellevurdert) 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.

    Emneord
    Cognitive work analysis, strategies analysis, automation, revolutionary systems design, long haul trucks
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-292799 (URN)10.1080/1463922X.2017.1278805 (DOI)000428728900006 ()
    Prosjekter
    MODAS
    Forskningsfinansiär
    VINNOVA, 2012-03678
    Tilgjengelig fra: 2017-01-27 Laget: 2016-05-09 Sist oppdatert: 2019-01-09bibliografisk kontrollert
  • 64.
    Axelsson, Anton
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Knowledge elicitation as abstraction of purposive behaviour2019Doktoravhandling, med artikler (Annet vitenskapelig)
    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.

    Delarbeid
    1. Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    Åpne denne publikasjonen i ny fane eller vindu >>Eliciting strategies in revolutionary design: exploring the hypothesis of predefined strategy categories
    2018 (engelsk)Inngår i: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 19, nr 1, s. 101-117Artikkel i tidsskrift (Fagfellevurdert) 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.

    Emneord
    Cognitive work analysis, strategies analysis, automation, revolutionary systems design, long haul trucks
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-292799 (URN)10.1080/1463922X.2017.1278805 (DOI)000428728900006 ()
    Prosjekter
    MODAS
    Forskningsfinansiär
    VINNOVA, 2012-03678
    Tilgjengelig fra: 2017-01-27 Laget: 2016-05-09 Sist oppdatert: 2019-01-09bibliografisk kontrollert
    2. Collegial verbalisation — the value of an independent observer: an ecological approach
    Åpne denne publikasjonen i ny fane eller vindu >>Collegial verbalisation — the value of an independent observer: an ecological approach
    2015 (engelsk)Inngår i: Theoretical Issues in Ergonomics Science, ISSN 1463-922X, E-ISSN 1464-536X, Vol. 16, nr 5, s. 474-494Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-249009 (URN)10.1080/1463922X.2015.1027322 (DOI)
    Tilgjengelig fra: 2015-04-07 Laget: 2015-04-09 Sist oppdatert: 2019-01-09bibliografisk kontrollert
    3. On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise
    Åpne denne publikasjonen i ny fane eller vindu >>On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise
    2018 (engelsk)Inngår i: Journal of Applied Research in Memory and Cognition, ISSN 2211-3681, E-ISSN 2211-369X, Vol. 7, nr 1, s. 51-59Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-352734 (URN)10.1016/j.jarmac.2017.12.004 (DOI)000429489400010 ()
    Forskningsfinansiär
    Swedish Transport Administration
    Tilgjengelig fra: 2018-03-03 Laget: 2018-06-07 Sist oppdatert: 2019-01-09bibliografisk kontrollert
    4. Experience and Visual Expertise: A First Look at Eye Behaviour in Train Traffic Control
    Åpne denne publikasjonen i ny fane eller vindu >>Experience and Visual Expertise: A First Look at Eye Behaviour in Train Traffic Control
    (engelsk)Inngår i: Artikkel i tidsskrift (Fagfellevurdert) 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.

    Emneord
    visual expertise, eye tracking, experience, train traffic control, rail human factors
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-372696 (URN)
    Forskningsfinansiär
    Swedish Transport Administration
    Tilgjengelig fra: 2019-01-08 Laget: 2019-01-08 Sist oppdatert: 2019-01-09
  • 65.
    Axelsson, Anton
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    A. Jansson, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    On the importance of mental time frames: A case for the need of empirical methods to investigate adaptive expertise2018Inngår i: Journal of Applied Research in Memory and Cognition, ISSN 2211-3681, E-ISSN 2211-369X, Vol. 7, nr 1, s. 51-59Artikkel i tidsskrift (Fagfellevurdert)
  • 66.
    Axelsson, Anton
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    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 preschoolers2016Inngår i: Journal of Educational Psychology, ISSN 0022-0663, E-ISSN 1939-2176, Vol. 108, nr 7, s. 969-981Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 67.
    Ayyalasomayajula, Kalyan Ram
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Learning based segmentation and generation methods for handwritten document images2019Doktoravhandling, med artikler (Annet vitenskapelig)
    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.

    Delarbeid
    1. Document binarization using topological clustering guided Laplacian Energy Segmentation
    Åpne denne publikasjonen i ny fane eller vindu >>Document binarization using topological clustering guided Laplacian Energy Segmentation
    2014 (engelsk)Inngår i: Proceedings International Conference on Frontiers in Handwriting Recognition (ICFHR), 2014, 2014, s. 523-528Konferansepaper, Publicerat paper (Fagfellevurdert)
    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.

    Serie
    Frontiers in Handwriting Recognition, ISSN 2167-6445 ; 14
    Emneord
    Image Processing; Classification; Machine Learning; Graph-theoretic methods.
    HSV kategori
    Forskningsprogram
    Datavetenskap
    Identifikatorer
    urn:nbn:se:uu:diva-238316 (URN)10.1109/ICFHR.2014.94 (DOI)978-1-4799-4335-7 (ISBN)
    Konferanse
    International Conference on Frontiers in Handwriting Recognition (ICFHR),September 1-4, 2014, Crete, Greece.
    Forskningsfinansiär
    Swedish Research Council, 2012-5743
    Tilgjengelig fra: 2014-12-11 Laget: 2014-12-11 Sist oppdatert: 2019-03-19bibliografisk kontrollert
    2. Historical document binarization combining semantic labeling and graph cuts
    Åpne denne publikasjonen i ny fane eller vindu >>Historical document binarization combining semantic labeling and graph cuts
    2017 (engelsk)Inngår i: Image Analysis: Part I, Springer, 2017, s. 386-396Konferansepaper, Publicerat paper (Fagfellevurdert)
    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.

    sted, utgiver, år, opplag, sider
    Springer, 2017
    Serie
    Lecture Notes in Computer Science, ISSN 0302-9743 ; 10269
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-335335 (URN)10.1007/978-3-319-59126-1_32 (DOI)000454359300032 ()978-3-319-59125-4 (ISBN)
    Konferanse
    SCIA 2017, June 12–14, Tromsø, Norway
    Forskningsfinansiär
    Swedish Research Council, 2012-5743Riksbankens Jubileumsfond, NHS14-2068:1
    Tilgjengelig fra: 2017-05-19 Laget: 2017-12-04 Sist oppdatert: 2019-03-19bibliografisk kontrollert
    3. PDNet: Semantic segmentation integrated with a primal-dual network for document binarization
    Åpne denne publikasjonen i ny fane eller vindu >>PDNet: Semantic segmentation integrated with a primal-dual network for document binarization
    2019 (engelsk)Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 121, s. 52-60Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-366933 (URN)10.1016/j.patrec.2018.05.011 (DOI)000459876700008 ()
    Forskningsfinansiär
    Swedish Research Council, 2012-5743Riksbankens Jubileumsfond, NHS14-2068:1
    Tilgjengelig fra: 2018-05-16 Laget: 2018-11-27 Sist oppdatert: 2019-04-04bibliografisk kontrollert
    4. Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models
    Åpne denne publikasjonen i ny fane eller vindu >>Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models
    2016 (engelsk)Inngår i: Advances in Visual Computing: Part I, Springer, 2016, s. 278-287Konferansepaper, Publicerat paper (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Springer, 2016
    Serie
    Lecture Notes in Computer Science ; 10072
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-308662 (URN)10.1007/978-3-319-50835-1_26 (DOI)978-3-319-50834-4 (ISBN)
    Konferanse
    ISVC 2016, December 12–14, Las Vegas, NV
    Prosjekter
    q2b – From Quill to Bytes
    Tilgjengelig fra: 2016-12-10 Laget: 2016-11-29 Sist oppdatert: 2019-03-19bibliografisk kontrollert
    5. CalligraphyNet: Augmenting handwriting generation with quill based stroke width
    Åpne denne publikasjonen i ny fane eller vindu >>CalligraphyNet: Augmenting handwriting generation with quill based stroke width
    2019 (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    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.

    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-379633 (URN)
    Konferanse
    26th IEEE International Conference on Image Processing
    Merknad

    Currently under review

    Tilgjengelig fra: 2019-03-19 Laget: 2019-03-19 Sist oppdatert: 2019-04-08
  • 68.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Document Binarization Combining with Graph Cuts and Deep Neural Networks2017Konferansepaper (Annet vitenskapelig)
  • 69.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Document binarization using topological clustering guided Laplacian Energy Segmentation2014Inngår i: Proceedings International Conference on Frontiers in Handwriting Recognition (ICFHR), 2014, 2014, s. 523-528Konferansepaper (Fagfellevurdert)
    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.

  • 70.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Historical document binarization combining semantic labeling and graph cuts2017Inngår i: Image Analysis: Part I, Springer, 2017, s. 386-396Konferansepaper (Fagfellevurdert)
    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.

  • 71.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Semantic Labeling using Convolutional Networks coupled with Graph-Cuts for Document binarization2017Konferansepaper (Annet vitenskapelig)
  • 72.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Topological clustering guided document binarization2015Rapport (Annet vitenskapelig)
    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.

  • 73.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Malmberg, Filip
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    PDNet: Semantic segmentation integrated with a primal-dual network for document binarization2019Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 121, s. 52-60Artikkel i tidsskrift (Fagfellevurdert)
    Fulltekst tilgjengelig fra 2020-05-17 16:13
  • 74.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Nettelblad, Carl
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för beräkningsvetenskap.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Feature evaluation for handwritten character recognition with regressive and generative Hidden Markov Models2016Inngår i: Advances in Visual Computing: Part I, Springer, 2016, s. 278-287Konferansepaper (Fagfellevurdert)
  • 75.
    Ayyalasomayajula, Kalyan Ram
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Wilkinson, Tomas
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Malmberg, Filip
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Radiologi.
    Brun, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    CalligraphyNet: Augmenting handwriting generation with quill based stroke width2019Manuskript (preprint) (Annet vitenskapelig)
    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.

  • 76.
    Azar, Jimmy
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Automated Tissue Image Analysis Using Pattern Recognition2014Doktoravhandling, med artikler (Annet vitenskapelig)
    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.

    Delarbeid
    1. Microarray Core Detection by Geometric Restoration
    Åpne denne publikasjonen i ny fane eller vindu >>Microarray Core Detection by Geometric Restoration
    2012 (engelsk)Inngår i: Analytical Cellular Pathology, ISSN 0921-8912, E-ISSN 1878-3651, Vol. 35, nr 5-6, s. 381-393Artikkel i tidsskrift (Fagfellevurdert) 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.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-183618 (URN)10.3233/ACP-2012-0067 (DOI)000311675800005 ()22684152 (PubMedID)
    Tilgjengelig fra: 2012-10-30 Laget: 2012-10-30 Sist oppdatert: 2017-12-07bibliografisk kontrollert
    2. Blind Color Decomposition of Histological Images
    Åpne denne publikasjonen i ny fane eller vindu >>Blind Color Decomposition of Histological Images
    Vise andre…
    2013 (engelsk)Inngår i: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 32, nr 6, s. 983-994Artikkel i tidsskrift (Fagfellevurdert) 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.

    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-160312 (URN)10.1109/TMI.2013.2239655 (DOI)000319701800002 ()
    Tilgjengelig fra: 2011-10-21 Laget: 2011-10-21 Sist oppdatert: 2018-12-02
    3. Histological Stain Evaluation for Machine Learning Applications
    Åpne denne publikasjonen i ny fane eller vindu >>Histological Stain Evaluation for Machine Learning Applications
    2012 (engelsk)Inngår i: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention, 2012Konferansepaper, Publicerat paper (Fagfellevurdert)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-183619 (URN)
    Konferanse
    MICCAI 2012, the 15th International Conference on Medical Image Computing and Computer Assisted Intervention, October 1-5, 2012, Nice, France
    Tilgjengelig fra: 2012-10-30 Laget: 2012-10-30 Sist oppdatert: 2015-01-23
    4. Image segmentation and identification of paired antibodies in breast tissue
    Åpne denne publikasjonen i ny fane eller vindu >>Image segmentation and identification of paired antibodies in breast tissue
    2014 (engelsk)Inngår i: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, s. 647273:1-11Artikkel i tidsskrift (Fagfellevurdert) 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.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-229978 (URN)10.1155/2014/647273 (DOI)000338856800001 ()25061472 (PubMedID)
    Prosjekter
    eSSENCE
    Tilgjengelig fra: 2014-07-01 Laget: 2014-08-18 Sist oppdatert: 2017-12-05bibliografisk kontrollert
    5. Automated Classification of Glandular Tissue by Statistical Proximity Sampling
    Åpne denne publikasjonen i ny fane eller vindu >>Automated Classification of Glandular Tissue by Statistical Proximity Sampling
    2015 (engelsk)Inngår i: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, artikkel-id 943104Artikkel i tidsskrift (Fagfellevurdert) 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.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-230871 (URN)10.1155/2015/943104 (DOI)000362067400001 ()
    Tilgjengelig fra: 2014-09-01 Laget: 2014-09-01 Sist oppdatert: 2017-12-05bibliografisk kontrollert
  • 77.
    Azar, Jimmy
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Busch, Christer
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Molekylär och morfologisk patologi.
    Carlbom, Ingrid
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Histological Stain Evaluation for Machine Learning Applications2012Inngår i: Proceedings of the International Conference on Medical Image Computing and Computer Assisted Intervention, 2012Konferansepaper (Fagfellevurdert)
  • 78.
    Azar, Jimmy
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Busch, Christer
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för genetik och patologi.
    Carlbom, Ingrid
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Microarray Core Detection by Geometric Restoration2012Inngår i: Analytical Cellular Pathology, ISSN 0921-8912, E-ISSN 1878-3651, Vol. 35, nr 5-6, s. 381-393Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 79.
    Azar, Jimmy C.
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Simonsson, Martin
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Hast, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Image segmentation and identification of paired antibodies in breast tissue2014Inngår i: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, s. 647273:1-11Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 80.
    Azar, Jimmy
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Simonsson, Martin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Hast, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Automated Classification of Glandular Tissue by Statistical Proximity Sampling2015Inngår i: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, artikkel-id 943104Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 81.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Single image super-resolution reconstruction in presence of mixed Poisson-Gaussian noise2016Inngår i: 2016 SIXTH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA), IEEE, 2016Konferansepaper (Fagfellevurdert)
    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.

  • 82.
    Bajic, Buda
    et al.
    Univ Novi Sad, Fac Tech Sci, Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sparsity promoting super-resolution coverage segmentation by linear unmixing in presence of blur and noise2019Inngår i: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 28, nr 1, artikkel-id 013046Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    We present a segmentation method that estimates the relative coverage of each pixel in a sensed image by each image component. The proposed super-resolution blur-aware model (utilizes a priori knowledge of the image blur) for linear unmixing of image intensities relies on a sparsity promoting approach expressed by two main requirements: (i) minimization of Huberized total variation, providing smooth object boundaries and noise removal, and (ii) minimization of nonedge image fuzziness, responding to an assumption that imaged objects are crisp and that fuzziness is mainly due to the imaging and digitization process. Edge fuzziness due to partial coverage is allowed, enabling subpixel precise feature estimates. The segmentation is formulated as an energy minimization problem and solved by the spectral projected gradient method, utilizing a graduated nonconvexity scheme. Quantitative and qualitative evaluation on synthetic and real multichannel images confirms good performance, particularly relevant when subpixel precision in segmentation and subsequent analysis is a requirement. (C) 2019 SPIE and IS&T

  • 83.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Sladoje, Nataša
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia.
    Blind restoration of images degraded with mixed poisson-Gaussian noise with application in transmission electron microscopy2016Inngår i: 2016 Ieee 13Th International Symposium On Biomedical Imaging (ISBI), IEEE, 2016, s. 123-127Konferansepaper (Fagfellevurdert)
    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.

  • 84.
    Bajic, Buda
    et al.
    Faculty of Technical Sciences, University of Novi Sad, Serbia.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Sladoje, Nataša
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Mathematical Institute, Serbian Academy of Sciences and Arts, Belgrade, Serbia.
    Restoration of images degraded by signal-dependent noise based on energy minimization: an empirical study2016Inngår i: Journal of Electronic Imaging (JEI), ISSN 1017-9909, E-ISSN 1560-229X, Vol. 25, nr 4, artikkel-id 043020Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 85. Bajic, Buda
    et al.
    Suveer, Amit
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Gupta, Anindya
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Pepic, Ivana
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sladoje, Natasa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sintorn, Ida-Maria
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Denoising of short exposure transmission electron microscopy images for ultrastructural enhancement2018Inngår i: Proc. 15th International Symposium on Biomedical Imaging, IEEE, 2018, s. 921-925Konferansepaper (Fagfellevurdert)
  • 86. Bajić, Buda
    et al.
    Lindblad, Joakim
    Sladoje, Nataša
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    An evaluation of potential functions for regularized image deblurring2014Inngår i: Image Analysis and Recognition: Part I, Springer Berlin/Heidelberg, 2014, s. 150-158Konferansepaper (Fagfellevurdert)
  • 87.
    Barrera, Tony
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Hast, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    A chronological and mathematical overview of digital circle generation algorithms: Introducing efficient 4- and 8-connected circles2016Inngår i: International Journal of Computer Mathematics, ISSN 0020-7160, E-ISSN 1029-0265, Vol. 93, nr 8, s. 1241-1253Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 88. Barrera, Tony
    et al.
    Hast, Anders
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    An Algorithm for Parallel Calculation of Trigonometric and Exponential Functions2013Inngår i: ACM International Conference on Computing Frontiers, 2013Konferansepaper (Fagfellevurdert)
  • 89. Beltrán-Castañón, César
    et al.
    Nyström, IngelaUppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.Famili, Fazel
    Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications2017Konferanseproceedings (Fagfellevurdert)
  • 90.
    Benedek, Nagy
    et al.
    University of Debrecen, Department of Computer Science, Debrecen Hungary .
    Strand, Robin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Normand, Nicolas
    Universit ́ de Nantes, IRCCyN UMR CNRS 6597, Nantes, France.
    A Weight Sequence Distance Function2013Inngår i: : Mathematical Morphology and Its Applications to Signal and Image Processing / [ed] Cris L. Luengo Hendriks, Gunilla Borgefors, Robin Strand, Springer Berlin/Heidelberg, 2013, s. 292-301Konferansepaper (Fagfellevurdert)
    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.

  • 91.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Image processing and its hardware support: Analysis vs synthesis - historical trends2017Inngår i: Image Analysis, SCIA 2017, Pt I / [ed] P Sharma, F M Bianchi, Switzerland, 2017, s. 3-14Konferansepaper (Fagfellevurdert)
    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.

  • 92.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Quantitative and automated microscopy: Where do we stand after 80 years of research?2014Inngår i: Proc. 11th International Symposium on Biomedical Imaging, Piscataway, NJ: IEEE Press, 2014, s. 274-277Konferansepaper (Fagfellevurdert)
  • 93.
    Bengtsson, Ewert
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Danielsen, Håvard
    Treanor, Darren
    Gurcan, Metin N.
    MacAulay, Calum
    Molnár, Béla
    Computer-aided diagnostics in digital pathology2017Inngår i: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 91, nr 6, s. 551-554Artikkel i tidsskrift (Annet vitenskapelig)
  • 94.
    Bengtsson, Ewert
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Malm, Patrik
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Screening for Cervical Cancer Using Automated Analysis of PAP-Smears2014Inngår i: Computational & Mathematical Methods in Medicine, ISSN 1748-670X, E-ISSN 1748-6718, Vol. 2014, s. 842037:1-12Artikkel, forskningsoversikt (Fagfellevurdert)
    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.

  • 95.
    Bengtsson, Ewert
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Ranefall, Petter
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Image analysis in digital pathology: Combining automated assessment of Ki67 staining quality with calculation of Ki67 cell proliferation index2019Inngår i: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 95, nr 7, s. 714-716Artikkel i tidsskrift (Annet vitenskapelig)
  • 96.
    Bengtsson, Ewert
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Tárnok, Attila
    Special Section on Image Cytometry2019Inngår i: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 95A, nr 4, s. 363-365Artikkel i tidsskrift (Annet vitenskapelig)
  • 97.
    Bengtsson, Ewert
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Reglerteknik. Uppsala university.
    Wieslander, Håkan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Forslid, Gustav
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Wählby, Carolina
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Hirsch, Jan-Michael
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för kirurgiska vetenskaper, Käkkirurgi.
    Runow Stark, Christina
    Kecheril Sadanandan, Sajith
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Lindblad, Joakim
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Detection of Malignancy-Associated Changes Due to Precancerous and Oral Cancer Lesions: A Pilot Study Using Deep Learning2018Inngår i: CYTO2018 / [ed] Andrea Cossarizza, 2018Konferansepaper (Fagfellevurdert)
    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.

  • 98. Bernander, Karl B.
    et al.
    Gustavsson, Kenneth
    Selig, Bettina
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Sintorn, Ida-Maria
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Luengo Hendriks, Cris L.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Improving the stochastic watershed2013Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, nr 9, s. 993-1000Artikkel i tidsskrift (Fagfellevurdert)
    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.

  • 99. Bernáld, Helena
    et al.
    Cajander, Åsa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Daniels, Mats
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik.
    Kultur, Can
    Löfström, Anette
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    McDermott, Roger
    Russell Dag, Lori
    Intercultural competence in global collaboration courses in computer engineering2012Inngår i: Advances in Design for Cross-Cultural Activities: Part I, Boca Raton, FL: CRC Press, 2012, s. 351-361Konferansepaper (Fagfellevurdert)
  • 100. Bernáld, Helena
    et al.
    Cajander, Åsa
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Daniels, Mats
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Datorteknik.
    Laxer, Cary
    Reasoning about the value of cultural awareness in international collaboration2011Inngår i: Journal of Applied Computing and Information Technology, ISSN 2230-4398, Vol. 15, nr 1:I2Artikkel i tidsskrift (Fagfellevurdert)
1234567 51 - 100 of 924
RefereraExporteraLink til resultatlisten
Permanent link
Referera
Referensformat
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Annet format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annet språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf