uu.seUppsala universitets publikasjoner
Endre søk
Begrens søket
3456789 251 - 300 of 823
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.
  • 251.
    Heil, Raphaela
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Vats, Ekta
    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.
    Exploring the Applicability of Capsule Networks for WordSpotting in Historical Handwritten Manuscripts2018Konferansepaper (Annet vitenskapelig)
  • 252.
    Heil, Raphaela
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Vats, Ekta
    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.
    Word Spotting in Historical Handwritten Manuscripts using Capsule Networks2018Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    Word spotting is popularly used for digitisation and transcription of historical handwritten documents. Recently, deep learning based methods have dominated the current state-of-the-art in learning-based word spotting. However, deep learning architectures such as Convolutional Neural Networks (CNNs) require a large amount of training data, and suffer from translation invariance. Capsule Networks (CapsNet) have been recently introduced as a data-efficient alternative to CNNs. This work explores the applicability of CapsNets for segmentation-based word spotting, and is the first such effort in the Handwritten Text Recognition (HTR) community to the best of authors' knowledge. The effectiveness of CapsNets will be empirically evaluated on well-known historical handwritten datasets using standard evaluation measures. The impact of varying amounts of training data on the recognition performance will be investigated, along with a comparison with the state-of-the-art methods.

  • 253.
    Hesse, Sara
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Holmin, Johan
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Entreprenörers hantering av bergmodeller i E4 Förbifart Stockholm: En studie över hur utformningen av modell påverkar produktionen2017Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    The goal of this master thesis is to study the challenges the contractors are experiencing when building in the project E4 The Stockholm Bypass (E4 Förbifart Stockholm) by using digital models. This is the first step for The Swedish Transport Administration towards the process of implementing BIM in the construction industry, which has led to several challenges and therefore is important to evaluate. The work of building E4 The Stockholm bypass can be seen with a sociotechnical perspective, since both humans and complex technology systems are involved in the project.

    The study used a qualitative method by interviewing the contractors, the promoters of the model and The Swedish Transport Administration. Furthermore, workshops were held with construction managers, BIM- specialists and the contractors’ measurement surveyors. The results were analysed by the theories regarding Human-Technology-Organisation (HTO), Human-Technology Interaction (HCI) with focus on usability and information management.

    The study resulted in a couple of recommendation to The Swedish Transport Administration. The main aspects were to involve the contractors earlier in the development of the models; have easily available information in the models necessary for production; change the contractors sceptical attitude towards BIM by listening to their issues; have a clear communication through the existing informations paths and create a common standard of format regarding exchange of information. By following the recommendations, the challenges regarding the work of the contractor will decrease and the implementation of models and BIM could proceed more efficiently. 

  • 254.
    Hirsch, Linda
    et al.
    Uppsala universitet, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Samhällsvetenskapliga fakulteten, Institutionen för informatik och media.
    Björsell, Anton
    Uppsala universitet, Humanistisk-samhällsvetenskapliga vetenskapsområdet, Samhällsvetenskapliga fakulteten, Institutionen för informatik och media.
    Laaksoharju, Mikael
    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.
    Obaid, Mohammad
    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.
    Investigating design implications towards a social robot as a memory trainer2017Inngår i: Proc. 5th International Conference on Human Agent Interaction, New York: ACM Press, 2017, s. 5-10Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Most currently existing tools for cognitive memory therapy require physical interaction or at least the presence of another person. The goal of this paper is to investigate whether a social robot might be an acceptable solution for a more inclusive therapy for people with memory disorder and severe physical limitations. Applying a user-centered design approach, we conducted semi-structured interviews with five healthcare professionals; four medical doctors and a psychologist, in three iterations followed by a focus group activity. An analysis of the collected data suggests several implications for design with an emphasis on embodiment, social skills, interaction, and memory training exercises.

  • 255.
    Holm, Malin
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Simulating Dialysis: Concept Evaluation of a PC Training Simulator for Nurses2013Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    Nurses at a haemodialysis clinic are required to handle complex technological equipment in a stressful environment, with the patients’ lives at risk. A training needs analysis (TNA) that was made at Karolinska University Hospital Huddinge in 2010 identifies the nurses’ need to practice alarm situations in the safe environment of a computer-based training simulator. This project builds on the conclusions of the TNA and the aim is to evaluate the concept of a training simulator by developing and evaluating a prototype program.

    The simulation model used is the prototype is based on a problem solving approach with virtual patient scenarios. During the entire development process continuous input has been gathered from nurses who work with dialysis. The project was completed by structured user test focusing on evaluating the usability and realism of the prototype.

    The conclusion of the project is that nurses working with dialysis need to practice alarm situations and that a training simulator could meet this need.

    The report is written in English.

  • 256.
    Holst, David
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    DICOM Second Generation RT: An Analysis of New Radiation Concepts by way of First-Second Generation Conversion2019Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    The current DICOM communication standard for radiotherapy is outdated and has serious design issues. A new version of the standard, known as DICOM 2nd generation for Radiotherapy, has been introduced and this thesis examines new concepts relating to radiation delivery. Firstly, some background into the practice of radiotherapy is given, as well as a description of the DICOM standard. Secondly, the thesis describes the design issues of the current standard and how the 2nd generation aims to solve these. Thirdly, the thesis explores the conversion of a first generation C-Arm Photon/Electron treatment plan to the second generation RT Radiation and RT Radiation Set IODs. A converter is implemented based on a model proposed in a previous work. With some simplifications, the conversion of Basic Static and Arc treatment plans is shown to be successful. Conversion of further dynamic plan types is judged to be fairly simple to implement following the same methodology. The conversion model’s efficacy and testability are discussed and while the model is flexible and facilitates extension to further modalities some areas of improvement are suggested. Lastly, a GUI for the converter is demonstrated and the possibilities of user interaction during conversion are discussed. 

  • 257. Holzwarth, Karolin
    et al.
    Köhler, Ralf
    Philipsen, Lars
    Tokoyoda, Koji
    Ladyhina, Valeriia
    Wählby, Carolina
    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.
    Niesner, Raluca A.
    Hauser, Anja E.
    Multiplexed fluorescence microscopy reveals heterogeneity among stromal cells in mouse bone marrow sections2018Inngår i: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 93, nr 9, s. 876-888Artikkel i tidsskrift (Fagfellevurdert)
  • 258.
    Hägg, Ragnar
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Scalable High Efficiency Video Coding: Cross-layer optimization2015Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    In July 2014, the second version of the HEVC/H.265 video coding standard was announced, and it included the Scalable High efficiency Video Coding (SHVC) extension. SHVC is used for coding a video stream with subset streams of the same video with lower quality, and it supports spatial, temporal and SNR scalability among others. This is used to enable easy adaption of a video stream, by dropping or adding packages, to devices with different screen sizes, computing power and bandwidth. In this project SHVC has been implemented in Ericsson's research encoder C65. Some cross-layer optimizations have also been implemented and evaluated. The main goal of these optimizations are to make better decisions when choosing the reference layer's motion parameters and QP, by doing multi-pass coding and using the coded enhancement layer information from the first pass.

  • 259.
    Hägg Sylvén, Ylva
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Requirement Analysis and Design of an Internet Portal for Intervention Studies2016Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    The evolution of technology has made it possible to provide Internet interventions to reduce unwanted symptoms of psychological distress and improve patients’ health. However, Internet interventions are complex and consist of several components that need to function in order to make interventions successful. One component is the interface of the platform where the interventions are created, delivered and evaluated. The platform needs to be designed for the users and the focus should be on the utility in order for the interventions to be successful. The strategic research programme U-CARE at Uppsala University has developed a platform, the U-CARE Portal, to deliver and evaluate interventions via the Internet. The task of designing the intervention studies on the Portal was perceived by the users to be difficult. The users often needed support in order to perform the task correctly. The aim of the thesis was to perform a requirement analysis in order to get an understanding on how to improve the interface of the study design, and then use the requirements in a design proposal for a more intuitive redesign. Four users designed test studies on the Portal during interviews. The material from the interviews formed the basis of the requirements, which were fulfilled with different design solutions in a design proposal. It was then modified through three iterations where the users commented on a paper prototype of the design.

  • 260.
    Häggblom, Jonas
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Bergman, Andreas
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Möjligheter och hinder i vidareutnyttjandet och tillgängliggörandet av öppna data i Örebro kommun2016Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [sv]

    Det huvudsakliga syftet med denna studie är att öka förutsättningarna för Örebro kommun att bedriva ett framgångsrikt arbete med öppna data. Genom att analysera nuläget med avseende på öppna data, dels nationellt, dels inom kommunen, ämnar studien att presentera ett antal rekommenderade strategiska åtgärder som bedöms vara lämpliga för att förbättra arbetet med öppna data i Örebro kommun. Rapporten ska, förutom att fylla ett utbildande syfte internt, utgöra ett underlag för framtida beslut angående öppna data centralt inom kommunen och i kommunens förvaltningar. Två workshopar och intervjuer med interna och externa aktörer genomfördes för att identifiera utmaningar, potentiella målbilder och aktiviteter relaterade till öppna data inom Örebro kommun. Dessa analyserades utifrån tidigare forskning om öppna data i offentliga organisationer. Resultaten visar att kommunen i Örebro bör öka den organisatoriska förmågan, skapa engagemang hos medborgare och underhålla en mer målorienterad strategi för öppna data.

  • 261.
    Hökars, Felicia
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Förutsättningar för utveckling av självkörande skyttelbussar i kollektivtrafiken2019Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    The most sustainable way to incorporate self-driving vehicles into our transportation system is to combine them with high capacity public transport. Unlike other forms of self-driving vehicles, in recent years self-driving shuttles have been tested to provide shorter transportation services. In a near future these shuttles could serve as feeders to and from stations, which will increase accessibility to public transport for more people. A first aim of this study was to examine the conditions for future development and use of self-driving shuttles as a complement to public transport in Sweden. The theoretical framework Technological Innovation Systems (TIS) was used in order to analyze the development. A second aim of this study was to examine whether TIS is appropriate for answering the first aim. Qualitative interviews were conducted with representatives from actor groups that were considered important for the development. The thesis suggest that the development is in a demonstration phase. The pilot tests with self-driving shuttles have played an important role in order to coordinate actors and create networks for knowledge diffusion. Identified blocking mechanism found are the complicated process of obtaining permission for conducting tests and uncertainties around technology development and use. In order to reach a niche market phase and commercialization the study suggest a continued support for more pilot tests and simplification of the permission process.

  • 262.
    Hörding, Olga
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    A comparative study between user research in academia and user research in commercially driven companies2015Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    The following degree project is written within the department of Information Technology at Uppsala University. The subject studied is the difference between academic user research and such user research performed by professionals at commercially driven companies. Academic’s and professional’s agendas, interests and approaches seem to differ and consequently a gap emerges. To perform a comparison between academically defined and practically defined user research a case study and a literature study were conducted. During the literature study three main academic approaches to perform user research were studied and summarized in a unified view. The case study was performed over 4 months at Spotify in the User Research team to gain insights into how user research is conducted in a commercially driven company. The degree project shows that academics and professionals can benefit from each other. For example, academics can integrate various mix methods to better understand design and concepts and base assumptions on more reliable data. Professionals can benefit from academics by adapting a similar systematic approach to perform user research and have a larger impact on the development.

  • 263.
    Ilic, Vladimir
    et al.
    Faculty of Engineering, 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. Faculty of Engineering, University of Novi Sad, Serbia.
    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. Faculty of Engineering, University of Novi Sad, Serbia.
    Precise Euclidean distance transforms in 3D from voxel coverage representation2015Inngår i: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 65, s. 184-191Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Distance transforms (DTs) are, usually, defined on a binary image as a mapping from each background element to the distance between its centre and the centre of the closest object element. However, due to discretization effects, such DTs have limited precision, including reduced rotational and translational invariance. We show in this paper that a significant improvement in performance of Euclidean DTs can be achieved if voxel coverage values are utilized and the position of an object boundary is estimated with sub-voxel precision. We propose two algorithms of linear time complexity for estimating Euclidean DT with sub-voxel precision. The evaluation confirms that both algorithms provide 4-14 times increased accuracy compared to what is achievable from a binary object representation.

  • 264.
    Ilic, Vladimir
    et al.
    Faculty of Technical Sciences, University of Novi Sad, 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, Serbi.
    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, Serbi.
    Signature of a Shape Based on Its Pixel Coverage Representation2016Inngår i: Discrete Geometry for Computer Imagery, DGCI 2016. Lecture Notes in Computer Science, Vol. 9647, pp. 181-193, Springer 2016: 19th IAPR International Conference, DGCI 2016, Nantes, France, April 18-20, 2016. Proceedings / [ed] Normand, Nicolas, Guédon, Jeanpierre, Autrusseau, Florent, Springer Berlin/Heidelberg, 2016, Vol. 9647, s. 181-193Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Distance from the boundary of a shape to its centroid, a.k.a. signature of a shape, is a frequently used shape descriptor. Commonly, the observed shape results from a crisp (binary) segmentation of an image. The loss of information associated with binarization leads to a significant decrease in accuracy and precision of the signature, as well as its reduced invariance w.r.t. translation and rotation. Coverage information enables better estimation of edge position within a pixel. In this paper, we propose an iterative method for computing the signature of a shape utilizing its pixel coverage representation. The proposed method iteratively improves the accuracy of the computed signature, starting from a good initial estimate. A statistical study indicates considerable improvements in both accuracy and precision, compared to a crisp approach and a previously proposed approach based on averaging signatures over α-cuts of a fuzzy representation. We observe improved performance of the proposed descriptor in the presence of noise and reduced variation under translation and rotation.

  • 265.
    Isaksson-Lutteman, Gunnika
    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.
    Future Train Traffic Control: Development and deployment of new principles and systems in train traffic control2012Licentiatavhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    The train traffic control system of the future requires new solutions and strategies in order to better meet tomorrow’s demands and goals. Uppsala University and Trafikverket have been collaborating for several years in research regarding train traffic control and how to improve traffic controllers’ support systems and working environment. At an early stage in the collaboration studies and analysis of important aspects of the traffic controller’s tasks, strategies, decision making, use of information and support systems were undertaken. This research resulted in new control paradigms, from control by exception to control by replanning. By using this paradigm we developed and designed prototype systems and interfaces that could better meet future goals and contribute to more optimal use of infrastructure capacity. Based on this research, a new operational traffic control system called STEG was developed in an iterative and user-centred design process. The system was deployed and tested operatively at a train traffic control centre in Sweden. The following evaluations focused on what happens when STEG is introduced in train traffic controllers’ work places. The evaluation of STEG showed satisfied users with a feeling of active involvement during the design and deployment processes, and gave confirmation that the new control strategies are functioning. STEG was seen as successful and was thereafter developed into MULTI-STEG, intended to be used by several users simultaneously, supporting them to share information in a new way. MULTI-STEG was deployed and tested at another train traffic control centre in Sweden. The following evaluations of MULTI-STEG focused on what happens when several users are involved and how train traffic controllers felt when sharing information, that before would have only been in their own minds, with each other. Some complications occurred due to mistakes in the deployment process, but altogether the evaluation showed positive attitudes towards the new system and MULTI-STEG was perceived as an efficient system for train traffic control.

    The main results are that STEG and MULTI-STEG can be used as an efficient train traffic control system and the new system can reduce the unnecessary cognitive load currently placed upon traffic controllers in today’s system. Also the deployment process is fundamental to the acceptance or non-acceptance of a new system by users. STEG was developed in a user-centred design process, but it is important that the deployment process is also user-centred.

    Delarbeid
    1. Development and implementation of new principles and systems for train traffic control in Sweden
    Åpne denne publikasjonen i ny fane eller vindu >>Development and implementation of new principles and systems for train traffic control in Sweden
    2010 (engelsk)Inngår i: Computers in Railways XII: Computer System Design and Operation in Railways and other Transit Systems, Southampton, UK: WIT Press , 2010, s. 441-450Konferansepaper, Publicerat paper (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Southampton, UK: WIT Press, 2010
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-150562 (URN)10.2495/CR100411 (DOI)978-1-84564-468-0 (ISBN)
    Tilgjengelig fra: 2011-03-31 Laget: 2011-03-31 Sist oppdatert: 2018-01-12bibliografisk kontrollert
    2. Operative tests of a new system for train traffic control
    Åpne denne publikasjonen i ny fane eller vindu >>Operative tests of a new system for train traffic control
    Vise andre…
    2009 (engelsk)Inngår i: Rail Human Factors around the World: Impacts on and of People for Successful Rail Operations / [ed] Dadashi, Nastaran, 2009, s. 424-433Konferansepaper, Publicerat paper (Annet vitenskapelig)
    Abstract [en]

    Tomorrow’s train traffic systems requires new strategies and solutions for efficient traintraffic control and utilization of track capacity, especially in traffic systems with a highdegree of deregulated and mixed traffic. There are many different goals associated withthe traffic control tasks and the work of the traffic controllers (dispatchers). Examples aresafety, efficiency of the traffic with regard to timeliness and energy consumption, goodservice and information to passengers and customers etc. Today’s traffic controlsystems and user interfaces do not efficiently support such goals. In earlier research wehave analyzed important aspects of the traffic controller’s tasks, strategies, decisionmaking, use of information and support systems etc. Based on this research we,together with Banverket (Swedish Rail Administration), have designed prototypesystems and interfaces that better can meet future goals and contribute to more optimaluse of infrastructure capacity. These prototype systems have now been developed into afully operational system which has been tested during 6 months, for control of train trafficin a section of the Swedish rail system. The evaluation shows that the system efficientlysupports control tasks and is well accepted by the involved traffic controllers.

    Emneord
    train traffic control, dispatchers, operator interface, decision support, situation awareness
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-169138 (URN)978-0-415-64475-4 (ISBN)
    Konferanse
    Third International Conference on Rail Human Factors, March 3-5, 2009, Lille, France
    Tilgjengelig fra: 2012-02-23 Laget: 2012-02-23 Sist oppdatert: 2018-01-12bibliografisk kontrollert
    3. Reducing unnecessary cognitive load in train traffic control
    Åpne denne publikasjonen i ny fane eller vindu >>Reducing unnecessary cognitive load in train traffic control
    2011 (engelsk)Konferansepaper, Publicerat paper (Annet vitenskapelig)
    Abstract [en]

    Uppsala University has collaborated with Swedish National Railway Administration in research about train traffic control and how to improve traffic controllers’ work environment, so that they can better meet future demands. This has resulted in a new operational train traffic control system called STEG. The traffic controllers are today forced to develop and use very complex mental models which take a long time to learn. We have also found that their cognitive capacity is more used to indentify, understand and analyze the traffic situation and less to solve problems and find optimal solutions to disturbances. The objective for developing STEG was to change this situation and reduce unnecessary cognitive load. Interviews with traffic controllers show that STEG has reduced the complexity of their mental models and contributed to less unnecessary cognitive load in operation. Our conclusion is that by reducing the complexity of their mental model, they can be skilled much faster and they are now able to use their cognitive capacity and skills on the important parts of their work.

    Emneord
    mental models, cognitive load, learning, operator interface, decision making, situation awareness, perception, train traffic control
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-169142 (URN)
    Konferanse
    Conference for work environment research, June 15-17, 2011, Luleå, Sweden
    Tilgjengelig fra: 2012-02-23 Laget: 2012-02-23 Sist oppdatert: 2018-01-12bibliografisk kontrollert
    4. All or nothing: Deployment must also be user-centred
    Åpne denne publikasjonen i ny fane eller vindu >>All or nothing: Deployment must also be user-centred
    2012 (engelsk)Inngår i: Ergonomics Open Journal, ISSN 1875-9343, E-ISSN 1875-9343Artikkel i tidsskrift (Annet vitenskapelig) Submitted
    Abstract [en]

    This article describes the importance ofusing a user-centred deployment process.The article is based on a case study of twotrain traffic control centres where the samesystem, STEG, was deployed with differentcontexts.

    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-169144 (URN)
    Tilgjengelig fra: 2012-02-23 Laget: 2012-02-23 Sist oppdatert: 2018-01-12bibliografisk kontrollert
  • 266.
    Ishaq, Omer
    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 Analysis and Deep Learning for Applications in Microscopy2016Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Quantitative microscopy deals with the extraction of quantitative measurements from samples observed under a microscope. Recent developments in microscopy systems, sample preparation and handling techniques have enabled high throughput biological experiments resulting in large amounts of image data, at biological scales ranging from subcellular structures such as fluorescently tagged nucleic acid sequences to whole organisms such as zebrafish embryos. Consequently, methods and algorithms for automated quantitative analysis of these images have become increasingly important. These methods range from traditional image analysis techniques to use of deep learning architectures.

    Many biomedical microscopy assays result in fluorescent spots. Robust detection and precise localization of these spots are two important, albeit sometimes overlapping, areas for application of quantitative image analysis. We demonstrate the use of popular deep learning architectures for spot detection and compare them against more traditional parametric model-based approaches. Moreover, we quantify the effect of pre-training and change in the size of training sets on detection performance. Thereafter, we determine the potential of training deep networks on synthetic and semi-synthetic datasets and their comparison with networks trained on manually annotated real data. In addition, we present a two-alternative forced-choice based tool for assisting in manual annotation of real image data. On a spot localization track, we parallelize a popular compressed sensing based localization method and evaluate its performance in conjunction with different optimizers, noise conditions and spot densities. We investigate its sensitivity to different point spread function estimates.

    Zebrafish is an important model organism, attractive for whole-organism image-based assays for drug discovery campaigns. The effect of drug-induced neuronal damage may be expressed in the form of zebrafish shape deformation. First, we present an automated method for accurate quantification of tail deformations in multi-fish micro-plate wells using image analysis techniques such as illumination correction, segmentation, generation of branch-free skeletons of partial tail-segments and their fusion to generate complete tails. Later, we demonstrate the use of a deep learning-based pipeline for classifying micro-plate wells as either drug-affected or negative controls, resulting in competitive performance, and compare the performance from deep learning against that from traditional image analysis approaches. 

    Delarbeid
    1. An Evaluation of the Faster STORM Method for Super-resolution Microscopy
    Åpne denne publikasjonen i ny fane eller vindu >>An Evaluation of the Faster STORM Method for Super-resolution Microscopy
    2014 (engelsk)Inngår i: Proceedings of the 22nd International Conference on Pattern Recognition, 2014, s. 4435-4440Konferansepaper, Publicerat paper (Fagfellevurdert)
    Abstract [en]

    Development of new stochastic super-resolution methods together with fluorescence microscopy imaging enables visualization of biological processes at increasing spatial and temporal resolution. Quantitative evaluation of such imaging experiments call for computational analysis methods that localize the signals with high precision and recall. Furthermore, it is desirable that the methods are fast and possible to parallelize so that the ever increasing amounts of collected data can be handled in an efficient way. We here in address signal detection in super-resolution microscopy by approaches based on compressed sensing. We describe how a previously published approach can be parallelized, reducing processing time at least four times. We also evaluate the effect of a greedy optimization approach on signal recovery at high noise and molecule density. Furthermore, our evaluation reveals how previously published compressed sensing algorithms have a performance that degrades to that of a random signal detector at high molecule density. Finally, we show the approximation of the imaging system's point spread function affects recall and precision of signal detection, illustrating the importance of parameter optimization. We evaluate the methods on synthetic data with varying signal to noise ratio and increasing molecular density, and visualize performance on realsuper-resolution microscopy data from a time-lapse sequence of livingcells.

    Serie
    International Conference on Pattern Recognition, ISSN 1051-4651
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-238600 (URN)10.1109/ICPR.2014.759 (DOI)000359818004096 ()978-1-4799-5208-3 (ISBN)
    Konferanse
    22nd International Conference on Pattern Recognition, 24-28 August, 2014S, tockholm, Sweden
    Tilgjengelig fra: 2014-12-14 Laget: 2014-12-14 Sist oppdatert: 2016-05-20bibliografisk kontrollert
    2. Evaluation of Deep Learning for Detection of Fluorescent Spots in Real Data
    Åpne denne publikasjonen i ny fane eller vindu >>Evaluation of Deep Learning for Detection of Fluorescent Spots in Real Data
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-283731 (URN)
    Tilgjengelig fra: 2016-04-14 Laget: 2016-04-14 Sist oppdatert: 2016-05-20
    3. Training of Machine Learning Methods for Fluorescent Spot Detection
    Åpne denne publikasjonen i ny fane eller vindu >>Training of Machine Learning Methods for Fluorescent Spot Detection
    (engelsk)Artikkel i tidsskrift (Fagfellevurdert) Submitted
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-283736 (URN)
    Tilgjengelig fra: 2016-04-14 Laget: 2016-04-14 Sist oppdatert: 2016-05-20
    4. Compaction of rolling circle amplification products increases signal integrity and signal–to–noise ratio
    Åpne denne publikasjonen i ny fane eller vindu >>Compaction of rolling circle amplification products increases signal integrity and signal–to–noise ratio
    Vise andre…
    2015 (engelsk)Inngår i: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, s. 12317:1-10, artikkel-id 12317Artikkel i tidsskrift (Fagfellevurdert) Published
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-260286 (URN)10.1038/srep12317 (DOI)000358358900001 ()26202090 (PubMedID)
    Forskningsfinansiär
    EU, FP7, Seventh Framework Programme, 278568EU, FP7, Seventh Framework Programme, 259796Swedish Research Council
    Tilgjengelig fra: 2015-07-23 Laget: 2015-08-18 Sist oppdatert: 2018-02-27bibliografisk kontrollert
    5. Bridging Histology and Bioinformatics: Computational analysis of spatially resolved transcriptomics
    Åpne denne publikasjonen i ny fane eller vindu >>Bridging Histology and Bioinformatics: Computational analysis of spatially resolved transcriptomics
    2017 (engelsk)Inngår i: Proceedings of the IEEE, ISSN 0018-9219, E-ISSN 1558-2256, Vol. 105, nr 3, s. 530-541Artikkel i tidsskrift (Fagfellevurdert) Published
    Abstract [en]

    It is well known that cells in tissue display a large heterogeneity in gene expression due to differences in cell lineage origin and variation in the local environment. Traditional methods that analyze gene expression from bulk RNA extracts fail to accurately describe this heterogeneity because of their intrinsic limitation in cellular and spatial resolution. Also, information on histology in the form of tissue architecture and organization is lost in the process. Recently, new transcriptome-wide analysis technologies have enabled the study of RNA molecules directly in tissue samples, thus maintaining spatial resolution and complementing histological information with molecular information important for the understanding of many biological processes and potentially relevant for the clinical management of cancer patients. These new methods generally comprise three levels of analysis. At the first level, biochemical techniques are used to generate signals that can be imaged by different means of fluorescence microscopy. At the second level, images are subject to digital image processing and analysis in order to detect and identify the aforementioned signals. At the third level, the collected data are analyzed and transformed into interpretable information by statistical methods and visualization techniques relating them to each other, to spatial distribution, and to tissue morphology. In this review, we describe state-of-the-art techniques used at all three levels of analysis. Finally, we discuss future perspective in this fast-growing field of spatially resolved transcriptomics.

    Emneord
    Biomedical image processing, biomedical signal analysis, computer-aided analysis, genetics, image analysis, image processing
    HSV kategori
    Forskningsprogram
    Datoriserad bildbehandling
    Identifikatorer
    urn:nbn:se:uu:diva-283723 (URN)10.1109/JPROC.2016.2538562 (DOI)000395894900011 ()
    Forskningsfinansiär
    Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceeSSENCE - An eScience CollaborationSwedish Research Council, 2012-4968 2014-00599
    Tilgjengelig fra: 2016-04-06 Laget: 2016-04-14 Sist oppdatert: 2017-04-27bibliografisk kontrollert
    6. Automated quantification of Zebrafish tail deformation for high-throughput drug screening
    Åpne denne publikasjonen i ny fane eller vindu >>Automated quantification of Zebrafish tail deformation for high-throughput drug screening
    Vise andre…
    2013 (engelsk)Inngår i: Proc. 10th International Symposium on Biomedical Imaging: From Nano to Macro, Piscataway, NJ: IEEE , 2013, s. 902-905Konferansepaper, Publicerat paper (Fagfellevurdert)
    sted, utgiver, år, opplag, sider
    Piscataway, NJ: IEEE, 2013
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-215457 (URN)10.1109/ISBI.2013.6556621 (DOI)000326900100226 ()978-1-4673-6456-0 (ISBN)
    Konferanse
    ISBI 2013, April 7-11, San Francisco, CA
    Tilgjengelig fra: 2013-04-11 Laget: 2014-01-14 Sist oppdatert: 2016-05-20bibliografisk kontrollert
    7. Deep Fish: Deep Learning-based Classification of Zebrafish Deformation for High-throughput Screening
    Åpne denne publikasjonen i ny fane eller vindu >>Deep Fish: Deep Learning-based Classification of Zebrafish Deformation for High-throughput Screening
    (engelsk)Manuskript (preprint) (Annet vitenskapelig)
    HSV kategori
    Identifikatorer
    urn:nbn:se:uu:diva-283738 (URN)
    Tilgjengelig fra: 2016-04-14 Laget: 2016-04-14 Sist oppdatert: 2016-05-20
  • 267.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Curic, Vladimir
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    Evaluation of Deep Learning for Detection of Fluorescent Spots in Real DataManuskript (preprint) (Annet vitenskapelig)
  • 268.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Curic, Vladimir
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    Training of Machine Learning Methods for Fluorescent Spot DetectionArtikkel i tidsskrift (Fagfellevurdert)
  • 269.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Biologiska sektionen, Institutionen för cell- och molekylärbiologi, Beräknings- och systembiologi.
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    An Evaluation of the Faster STORM Method for Super-resolution Microscopy2014Inngår i: Proceedings of the 22nd International Conference on Pattern Recognition, 2014, s. 4435-4440Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Development of new stochastic super-resolution methods together with fluorescence microscopy imaging enables visualization of biological processes at increasing spatial and temporal resolution. Quantitative evaluation of such imaging experiments call for computational analysis methods that localize the signals with high precision and recall. Furthermore, it is desirable that the methods are fast and possible to parallelize so that the ever increasing amounts of collected data can be handled in an efficient way. We here in address signal detection in super-resolution microscopy by approaches based on compressed sensing. We describe how a previously published approach can be parallelized, reducing processing time at least four times. We also evaluate the effect of a greedy optimization approach on signal recovery at high noise and molecule density. Furthermore, our evaluation reveals how previously published compressed sensing algorithms have a performance that degrades to that of a random signal detector at high molecule density. Finally, we show the approximation of the imaging system's point spread function affects recall and precision of signal detection, illustrating the importance of parameter optimization. We evaluate the methods on synthetic data with varying signal to noise ratio and increasing molecular density, and visualize performance on realsuper-resolution microscopy data from a time-lapse sequence of livingcells.

  • 270.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Kecheril Sadanandan, Sajith
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    Deep Fish: Deep Learning-based Classification of Zebrafish Deformation for High-throughput ScreeningManuskript (preprint) (Annet vitenskapelig)
  • 271.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Negri, Joseph
    Anthony, Mark-Bray
    Pacureanu, Alexandra
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. 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.
    Peterson, Randall
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    Image-based screening of zebrafish2013Konferansepaper (Annet vitenskapelig)
  • 272.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Negri, Joseph
    Bray, Mark-Anthony
    Pacureanu, Alexandra
    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.
    Peterson, Randall T.
    Wählby, Carolina
    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.
    Automated quantification of Zebrafish tail deformation for high-throughput drug screening2013Inngår i: Proc. 10th International Symposium on Biomedical Imaging: From Nano to Macro, Piscataway, NJ: IEEE , 2013, s. 902-905Konferansepaper (Fagfellevurdert)
  • 273.
    Ishaq, Omer
    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.
    Negri, Joseph
    Broad Institute of Harvard and MIT.
    Bray, Mark-Anthony
    Broad Institute of Harvard and MIT.
    Pacureanu, Alexandra
    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.
    Wählby, Carolina
    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.
    An image based high-throughput assay for chemical screening using zebrafish.2012Konferansepaper (Fagfellevurdert)
  • 274.
    Ishaq, Omer
    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, Science for Life Laboratory, SciLifeLab.
    Pacureanu, Alexandra
    Uppsala universitet, Science for Life Laboratory, SciLifeLab. 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.
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab.
    Light Tomography2013Konferansepaper (Annet vitenskapelig)
  • 275.
    Ishaq, Omer
    et al.
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Sadanandan, Sajith Kecheril
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    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.
    Deep Fish: Deep Learning-Based Classification of Zebrafish Deformation for High-Throughput Screening2017Inngår i: Journal of Biomolecular Screening, ISSN 1087-0571, E-ISSN 1552-454X, Vol. 22, nr 1, s. 102-107Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Zebrafish (Danio rerio) is an important vertebrate model organism in biomedical research, especially suitable for morphological screening due to its transparent body during early development. Deep learning has emerged as a dominant paradigm for data analysis and found a number of applications in computer vision and image analysis. Here we demonstrate the potential of a deep learning approach for accurate high-throughput classification of whole-body zebrafish deformations in multifish microwell plates. Deep learning uses the raw image data as an input, without the need of expert knowledge for feature design or optimization of the segmentation parameters. We trained the deep learning classifier on as few as 84 images (before data augmentation) and achieved a classification accuracy of 92.8% on an unseen test data set that is comparable to the previous state of the art (95%) based on user-specified segmentation and deformation metrics. Ablation studies by digitally removing whole fish or parts of the fish from the images revealed that the classifier learned discriminative features from the image foreground, and we observed that the deformations of the head region, rather than the visually apparent bent tail, were more important for good classification performance.

  • 276.
    Issac Niwas, Swamidoss
    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.
    Kårsnäs, Andreas
    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.
    Uhlmann, Virginie
    Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA, USA and Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
    Palanisamy, P.
    Dept. of Electronics and Communication Engineering (ECE), National Institute of Technology (NIT), Tiruchirappalli, India.
    Kampf, Caroline
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Molekylär och morfologisk patologi.
    Simonsson, Martin
    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.
    Wählby, Carolina
    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.
    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.
    Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas2012Inngår i: Histopathology Image Analysis (HIMA): a MICCAI 2012 workshop, 2012Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Background:

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/ ). It contains a large number of histological images of sections from human tissue. Tissue micro arrays are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples.

    Methods and Material:

    The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features and WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (SVM and LDA classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue.

    Results:

    Good results have been obtained by using the combinations of GLCM and wavelets and texture features, edge features, histograms, transforms, etc. (WND-CHARM). The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert.

    Conclusions:

    Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumour grading.

  • 277.
    Issac Niwas, Swamidoss
    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.
    Kårsnäs, Andreas
    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.
    Uhlmann, Virginie
    Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA, USA and Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
    Ponnusamy, Palanisamy
    Dept. of Electronics and Communication Engineering (ECE), National Institute of Technology (NIT), Tiruchirappalli, India.
    Kampf, Caroline
    Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för genetik och patologi, Molekylär och morfologisk patologi.
    Simonsson, Martin
    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.
    Wählby, Carolina
    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, Science for Life Laboratory, SciLifeLab. Broad Institute of Harvard and Massachusetts Institute Technology (MIT), Cambridge, Massachusetts, MA, USA, .
    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.
    Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas2013Inngår i: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 4, nr 14Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Background:

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples.

    Materials and Methods:

    The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue.

    Results:

    We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert.

    Conclusions:

    Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading.

  • 278.
    Issac Niwas, Swamidoss
    et al.
    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.
    Palanisamy, P
    National Institute of Technology (NIT), Tiruchirappalli, India.
    Bengtsson, Ewert
    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.
    An Investigation on Nuclei of Histopathological Images using Curvelet Statistical Features2012Konferansepaper (Annet vitenskapelig)
  • 279.
    Issac Niwas, Swamidoss
    et al.
    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.
    Palanisamy, P
    National Institute of Technology (NIT), Tiruchirappalli, India.
    Bengtsson, Ewert
    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.
    Color deconvolution method for breast tissue core biopsy images cell nuclei detection and analysis using multiresolution techniques2013Inngår i: International Journal of Imaging and Robotics, ISSN 2231-525X, Vol. 9, nr 1, s. 61-72Artikkel i tidsskrift (Fagfellevurdert)
  • 280.
    Issac Niwas, Swamidoss
    et al.
    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.
    Palanisamy, P
    National Institute of Technology (NIT), Tiruchirappalli, India.
    Sujathan, K
    Regional Cancer Centre, Thiruvanathapuram, India.
    Bengtsson, Ewert
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion.
    Analysis of nuclei textures of fine needle aspirated cytology images for breast cancer diagnosis using complex Daubechies wavelets2013Inngår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 93, nr 10, s. 2828-2837Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Breast cancer is the most frequent cause of cancer induced death among women in the world. Diagnosis of this cancer can be done through radiological, surgical, and pathological assessments of breast tissue samples. A common test for detection of this cancer involves visual microscopic inspection of Fine Needle Aspiration Cytology (FNAC) samples of breast tissue. The result of analysis on this sample by a cytopathologist is crucial for the breast cancer patient. For the assessment of malignancy, the chromatin texture patterns of the cell nuclei are essential. Wavelet transforms have been shown to be good tools for extracting information about texture. In this paper, it has been investigated whether complex wavelets can provide better performance than the more common real valued wavelet transform. The features extracted through the wavelets are used as input to a k-nn classifier. The correct classification results are obtained as 93.9% for the complex wavelets and 70.3% for the real wavelets.

  • 281.
    Iveroth, Axel
    Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion.
    Using Work Domain Analysis to Evaluate the Design of a Data Warehouse System2019Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [en]

    Being able to perform good data analysis is a fundamental part of running any business or organization. One way of enabling data analysis is with a data warehouse system, a type of database that gathers and transforms data from multiple sources and structures it in the goal of simplifying analysis. It is commonly used to provide support in decision-making.

    Although a data warehouse enables data analysis, it is also relevant to consider how well the system supports analysis. This thesis is a qualitative research that aims to investigate how work domain analysis (WDA) can be used to evaluate the design of a data warehouse system. To do so, a case study at the IT company Norconsult Astando was performed. A data warehouse system was designed for an issue management system and evaluated using the abstraction hierarchy (AH) model.

    The research done in this thesis showed that analysis was enabled by adopting Kimball’s bottom-up approach and a star schema design with an accumulating snapshot fact table. Through evaluation of the design, it was shown that most of the design choices made for the data warehouse were captured in the AH. It was concluded that with sufficient data collection methods, WDA can be used to a large extent when evaluating a data warehouse system.

  • 282.
    Janols, Rebecka
    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.
    Evolving Systems – Engaged Users: Key Principles for Improving Region-wide Health IT Adoption2013Doktoravhandling, med artikler (Annet vitenskapelig)
    Abstract [en]

    Many countries have formulated their eHealth visions and billions of dollars have been spent on supporting the eHealth development throughout the world. An important part of the development is the electronic patient record (EPR). To enable sharing and increase cooperation between care providers, most Swedish county councils have decided to use a region-wide EPR. The health professionals often experience numerous problems and consider the region-wide EPR to be too generic and require them to tailor their practices instead of the system evolving towards supporting their needs.

    The aim of the PhD research is to gain knowledge of adoption when deploying and using region-wide health IT systems. This is accomplished by studying, analysing and reflecting upon what region-wide health IT systems are and how professionals use them in their practice. In the research a grounded theory method has been used, which means that the empirical data, not theories and hypotheses, have driven the research process. The data-gathering methods have been interviews, observations, participating in meetings, questionnaires, seminars and conducting literature reviews.

    In order to be able to improve the adoption, a set of four key principles has been identified: (1) Evolving systems-Engaged users, (2) Treat IT deployment and usage as part of organisational development, (3) Identify, respect and support differences, and (4) Identify what must be customised and what can be centralised.

    These four principles challenge the traditional way of developing enterprise-wide IT and emphasise the importance that users must engage in the development, procurement and deployment process to identify their similar and unique needs and procedures. It is crucial that both the similarities and uniqueness are respected and supported. The similarities can be supported by a centralised, standardised solution, while uniqueness requires a customised solution. In order to accomplish that, the IT deployment and usage needs to be treated as an important part of the on-going organisational development, and the IT systems must evolve, i.e., be continuously developed in order to engage the users to participate. 

    Delarbeid
    1. Physicians' concept of time usage: A key concern in EPR deployment
    Åpne denne publikasjonen i ny fane eller vindu >>Physicians' concept of time usage: A key concern in EPR deployment