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  • 1.
    Abrate, Matteo
    et al.
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Bacciu, Clara
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Hast, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Marchetti, Andrea
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Minutoli, Salvatore
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Tesconi, Maurizio
    CNR Natl Res Council, Inst Informat & Telemat, I-56124 Pisa, Italy.
    Geomemories - A Platform for Visualizing Historical, Environmental and Geospatial Changes of the Italian Landscape2013In: ISPRS International Journal of Geo-Information. Special issue: Geospatial Monitoring and Modelling of Environmental Change, ISSN 2220-9964, Vol. 2, no 2, p. 432-455Article in journal (Refereed)
    Abstract [en]

    The GeoMemories project aims at publishing on the Web and digitally preserving historical aerial photographs that are currently stored in physical form within the archives of the Aerofototeca Nazionale in Rome. We describe a system, available at http://www.geomemories.org, that lets users visualize the evolution of the Italian landscape throughout the last century. The Web portal allows comparison of recent satellite imagery with several layers of historical maps, obtained from the aerial photos through a complex workflow that merges them together. We present several case studies carried out in collaboration with geologists, historians and archaeologists, that illustrate the great potential of our system in different research fields. Experiments and advances in image processing technologies are envisaged as a key factor in solving the inherent issue of vast amounts of manual work, from georeferencing to mosaicking to analysis.

  • 2. Adinugroho, Sigit
    et al.
    Vallot, Dorothée
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, LUVAL.
    Westrin, Pontus
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Calving events detection and quantification from time-lapse images in Tunabreen glacier2015In: Proc. 9th International Conference on Information & Communication Technology and Systems, Piscataway, NJ: IEEE , 2015, p. 61-65Conference paper (Refereed)
  • 3.
    Adler, Jeremy
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Parmryd, Ingela
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Cell Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Conventional analysis of movement on non-flat surfaces like the plasma membrane makes Brownian motion appear anomalous2019In: Communications Biology, E-ISSN 2399-3642, Vol. 2, article id 12Article in journal (Refereed)
  • 4.
    Agarwala, Sunita
    et al.
    Natl Inst Technol Durgapur, Comp Sci & Engn, Durgapur, India..
    Kumar, Abhishek
    Univ Hyderabad, Sch Comp & Informat Sci, Hyderabad, India..
    Nandi, Debashis
    Natl Inst Technol Durgapur, Comp Sci & Engn, Durgapur, India..
    Dhara, Ashis Kumar
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sadhu, Anup
    Med Coll Kolkata, Kolkata, India..
    Thakur, Sumitra Basu
    Med Coll Kolkata, Kolkata, India..
    Bhadra, Ashok Kumar
    Med Coll Kolkata, Kolkata, India..
    Convolutional Neural Networks for Efficient Localization of Interstitial Lung Disease Patterns in HRCT Images2018In: Medical Image Understanding and Analysis: 22nd Conference, MIUA 2018, Southampton, UK, July 9-11, 2018, Proceedings / [ed] Mark Nixon, Sasan Mahmoodi & Reyer Zwiggelaar, Springer Nature , 2018, p. 12-22Conference paper (Refereed)
    Abstract [en]

    Lung field segmentation is the first step towards the development of any computer aided diagnosis (CAD) system for interstitial lung diseases (ILD) observed in chest high resolution computed tomography (HRCT) images. If the segmentation is not done efficiently it will compromise the accuracy of CAD system. In this paper, a deep learning-based method is proposed to localize several interstitial lung disease patterns (ILD) in HRCT images without performing lung field segmentation. In this paper, localization of several ILD patterns is performed in image slice. The pretrained models of ZF and VGG networks were fine-tuned in order to localize ILD patterns using Faster R-CNN framework. The three most difficult ILD patterns consolidation, emphysema, and fibrosis have been used for this study and the accuracy of the method has been evaluated in terms of mean average precision (mAP) and free receiver operating characteristic (FROC) curve. The model achieved mAP value of 75% and 83% on ZF and VGG networks, respectively. The result obtained shows the effectiveness of the method in the localization of different ILD patterns.

  • 5. Agarwala, Sunita
    et al.
    Nandi, Debashis
    Kumar, Abhishek
    Dhara, Ashis Kumar
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Thakur, Sumitra Basu
    Sadhu, Anup
    Bhadra, Ashok Kumar
    Automated segmentation of lung field in HRCT images using active shape model2017In: Proc. 37th Region 10 Conference, IEEE, 2017, p. 2516-2520Conference paper (Refereed)
  • 6.
    Ahlberg, Sofie
    et al.
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Axelsson, Agnes
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Yu, Pian
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Cortez, Wenceslao Shaw
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Gao, Alex Yuan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Shenzhen Inst Artificial Intelligence & Robot Soc, Ctr Intelligent Robots, Shenzhen, Peoples R China..
    Ghadirzadeh, Ali
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Castellano, Ginevra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kragic, Danica
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Skantze, Gabriel
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Dimarogonas, Dimos, V
    KTH Royal Inst Technol, Dept Intelligent Syst, Stockholm, Sweden..
    Co-adaptive Human-Robot Cooperation: Summary and Challenges2022In: Scientific World Journal, E-ISSN 1537-744X, Vol. 10, no 02, p. 187-203Article in journal (Refereed)
    Abstract [en]

    The work presented here is a culmination of developments within the Swedish project COIN: Co-adaptive human-robot interactive systems, funded by the Swedish Foundation for Strategic Research (SSF), which addresses a unified framework for co-adaptive methodologies in human-robot co-existence. We investigate co-adaptation in the context of safe planning/control, trust, and multi-modal human-robot interactions, and present novel methods that allow humans and robots to adapt to one another and discuss directions for future work.

  • 7.
    Ahmad, Awais
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Cajander, Åsa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Johansson, Birgitta
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
    Ehrsson, Ylva Tiblom
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Otolaryngology and Head and Neck Surgery.
    Langegård, Ulrica
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Experimental and Clinical Oncology.
    Designing for Human Well-Being: A Case Study with Informal Caregivers of Individuals with Cancer2022In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 294, p. 214-218Article in journal (Refereed)
    Abstract [en]

    Informal Caregivers such as a spouse, other close relatives or friends of cancer patients can play an essential role in home-based treatment and care. However, the informal caregivers might not be prepared for this responsibility, and they might have several unmet requirements for taking care of patients in the home environment. The informal caregivers’ physical, social and psychological health is also profoundly affected due to the health conditions of their relatives. We propose a User-centred Positive Design as a hybrid framework by merging the traditional User-cantered design and positive design frameworks to enhance the informal caregivers’ subjective well-being. Our ongoing project (Carer-eSupport) will be used as a case study, and its main objective is to co-create and evaluate a web-based support system for informal caregivers of people with cancer. The proposed framework can be used for the design and development of health information systems with a special focus on users’ wellbeing and positive emotions.

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  • 8.
    Ahmad, Awais
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Premanandan, Shweta
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Cajander, Åsa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computing Education Research. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media.
    Improving Remote Examination Formats: Addressing Challenges and Providing Recommendations for University Educators in the Age of ChatGPT2024Conference paper (Refereed)
    Abstract [en]

    The availability of Large Language Models (LLM), such as the widely accessible ChatGPT, has raised concerns regarding the reliability of assessment formats in university education. This presentation sheds light on the potential impact of ChatGPT on existing remote examination formats and offers recommendations to overcome associated challenges. Through interviews with three computer science educators and an analysis of insights from blog posts, social media platforms, and academic forums, we gathered diverse opinions and experiences related to ChatGPT's impact on university assessment formats. Our findings reveal challenges, particularly in cheating prevention, prompting the need for educators to adapt their teaching methods to this evolving landscape. While GPT performs well in answering open-ended questions, it struggles with calculations and problem-solving, with multiple-choice questions posing additional challenges. Incorporating interactive activities and oral examinations should be prioritized in this context. As ChatGPT gains traction, institutions must address concerns to maintain academic integrity.

  • 9.
    Ahmad, Nouman
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Dahlberg, Hugo
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Jönsson, Hanna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Tarai, Sambit
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Guggilla, Rama Krishna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Lundström, Elin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Bergstrom, Goran
    Univ Gothenburg, Inst Med, Sahlgrenska Acad, Dept Mol & Clin Med, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Dept Clin Physiol, Reg Vastra Gotaland, Gothenburg, Sweden..
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Antaros Med, Mölndal, Sweden..
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Antaros Med, Mölndal, Sweden..
    Voxel-wise body composition analysis using image registration of a three-slice CT imaging protocol: methodology and proof-of-concept studies2024In: Biomedical engineering online, E-ISSN 1475-925X, Vol. 23, no 1, article id 42Article in journal (Refereed)
    Abstract [en]

    Background Computed tomography (CT) is an imaging modality commonly used for studies of internal body structures and very useful for detailed studies of body composition. The aim of this study was to develop and evaluate a fully automatic image registration framework for inter-subject CT slice registration. The aim was also to use the results, in a set of proof-of-concept studies, for voxel-wise statistical body composition analysis (Imiomics) of correlations between imaging and non-imaging data.Methods The current study utilized three single-slice CT images of the liver, abdomen, and thigh from two large cohort studies, SCAPIS and IGT. The image registration method developed and evaluated used both CT images together with image-derived tissue and organ segmentation masks. To evaluate the performance of the registration method, a set of baseline 3-single-slice CT images (from 2780 subjects including 8285 slices) from the SCAPIS and IGT cohorts were registered. Vector magnitude and intensity magnitude error indicating inverse consistency were used for evaluation. Image registration results were further used for voxel-wise analysis of associations between the CT images (as represented by tissue volume from Hounsfield unit and Jacobian determinant) and various explicit measurements of various tissues, fat depots, and organs collected in both cohort studies.Results Our findings demonstrated that the key organs and anatomical structures were registered appropriately. The evaluation parameters of inverse consistency, such as vector magnitude and intensity magnitude error, were on average less than 3 mm and 50 Hounsfield units. The registration followed by Imiomics analysis enabled the examination of associations between various explicit measurements (liver, spleen, abdominal muscle, visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), thigh SAT, intermuscular adipose tissue (IMAT), and thigh muscle) and the voxel-wise image information.Conclusion The developed and evaluated framework allows accurate image registrations of the collected three single-slice CT images and enables detailed voxel-wise studies of associations between body composition and associated diseases and risk factors.

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  • 10.
    Ahmad, Nouman
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sparresäter, Björn
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Tarai, Sambit
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Lundström, Elin
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Bergström, Göran
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Automatic segmentation of large-scale CT image datasets for detailed body composition analysis.2023In: BMC Bioinformatics, E-ISSN 1471-2105, Vol. 24, no 1, article id 346Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Body composition (BC) is an important factor in determining the risk of type 2-diabetes and cardiovascular disease. Computed tomography (CT) is a useful imaging technique for studying BC, however manual segmentation of CT images is time-consuming and subjective. The purpose of this study is to develop and evaluate fully automated segmentation techniques applicable to a 3-slice CT imaging protocol, consisting of single slices at the level of the liver, abdomen, and thigh, allowing detailed analysis of numerous tissues and organs.

    METHODS: The study used more than 4000 CT subjects acquired from the large-scale SCAPIS and IGT cohort to train and evaluate four convolutional neural network based architectures: ResUNET, UNET++, Ghost-UNET, and the proposed Ghost-UNET++. The segmentation techniques were developed and evaluated for automated segmentation of the liver, spleen, skeletal muscle, bone marrow, cortical bone, and various adipose tissue depots, including visceral (VAT), intraperitoneal (IPAT), retroperitoneal (RPAT), subcutaneous (SAT), deep (DSAT), and superficial SAT (SSAT), as well as intermuscular adipose tissue (IMAT). The models were trained and validated for each target using tenfold cross-validation and test sets.

    RESULTS: The Dice scores on cross validation in SCAPIS were: ResUNET 0.964 (0.909-0.996), UNET++ 0.981 (0.927-0.996), Ghost-UNET 0.961 (0.904-0.991), and Ghost-UNET++ 0.968 (0.910-0.994). All four models showed relatively strong results, however UNET++ had the best performance overall. Ghost-UNET++ performed competitively compared to UNET++ and showed a more computationally efficient approach.

    CONCLUSION: Fully automated segmentation techniques can be successfully applied to a 3-slice CT imaging protocol to analyze multiple tissues and organs related to BC. The overall best performance was achieved by UNET++, against which Ghost-UNET++ showed competitive results based on a more computationally efficient approach. The use of fully automated segmentation methods can reduce analysis time and provide objective results in large-scale studies of BC.

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  • 11.
    Ahmad, Shafqat
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Carrasquilla, Germán
    Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
    Langner, Taro
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Menzel, Uwe
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Hammar, Ulf
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Censin, Jenny C.
    Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; 7Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
    Sayols-Baixeras, Sergi
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Nguyen, Diem
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Mora, Andrés Martínez
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Eriksson, Jan W.
    Clinical Diabetes and Metabolism, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Fall, Tove
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Molecular epidemiology.
    Genetics of liver fat and volume associate with altered metabolism and whole body magnetic resonance imaging2022In: Journal of Hepatology, ISSN 0168-8278, E-ISSN 1600-0641, Vol. 77, p. S40-S40Article in journal (Other academic)
  • 12.
    Akkuzu, Anastasia
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Castellano, Ginevra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Calvo-Barajas, Natalia
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Behavioural Observations as Objective Measures of Trust in Child-Robot Interaction: Mutual Gaze2023In: HAI '23: Proceedings of the 11th International Conference on Human-Agent Interaction, Association for Computing Machinery (ACM), 2023, p. 452-454Conference paper (Refereed)
    Abstract [en]

    In developing a computational model of trust, this paper summarises the findings in a previous study exploring mutual gaze as a behavioural parameter of social trust and liking [1]. Drawing on the data collected in a related paper [6], which provides us with video clips of children interacting with a robot during a collaborative storytelling game, we look at the interactions between metrics assessing social trust and liking, and the development of mutual gaze as an objective measure of social trust and liking. We achieve this through several statistical analyses between the percent of mutual gaze in each interaction, scores from social trust and liking metrics, age of the participant, and duration. The findings of our study support the use of mutual gaze as an objective measure for liking, but there is still not sufficient evidence to support the use of mutual gaze as an objective measure to identify and capture social trust as a whole. Furthermore, interaction context impacts the amount of mutual gaze in an interaction, and the age of the participant has an impact on the amount of mutual gaze that occurs.

  • 13. Alenljung, Beatrice
    et al.
    Andreasson, Rebecca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lowe, Robert
    Billing, Erik
    Lindblom, Jessica
    Conveying Emotions by Touch to the Nao Robot: A User Experience Perspective2018In: Multimodal Technologies and Interaction, ISSN 2414-4088, Vol. 2, no 4, article id 82Article in journal (Refereed)
    Abstract
  • 14. Alenljung, Beatrice
    et al.
    Lindblom, Jessica
    Andreasson, Rebecca
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Ziemke, Tom
    User experience in social human–robot interaction2017In: International Journal of Ambient Computing and Intelligence (IJACI), ISSN 1941-6237, E-ISSN 1941-6245, Vol. 8, no 2, p. 12-31Article in journal (Refereed)
    Abstract
  • 15.
    Alenljung, Beatrice
    et al.
    Univ Skovde, Hogskolevagen, S-54128 Skovde, Sweden..
    Lindblom, Jessica
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Zaragoza-Sundqvist, Maximiliano
    AstraZeneca R&D, S-43183 Molndal, Sweden..
    Hanna, Atieh
    Volvo AB, S-40508 Gothenburg, Sweden..
    Towards a Framework of Human-Robot Interaction Strategies from an Operator 5.0 Perspective2023In: Advances in Manufacturing Technology XXXVI / [ed] Andrew Thomas;Lyndon Murphy;Wyn Morris;Vincenzo Dispenza;David Jones, IOS Press, 2023, Vol. 44, p. 81-86Conference paper (Refereed)
    Abstract [en]

    The industrial transition to Industrie 4.0 and subsequently Industrie 5.0 requires robots to be able to share physical and social space with humans in such a way that interaction and coexistence are positively experienced by the humans and where it is possible for the human and the robot to mutually perceive, interpret and act on each other's actions and intentions. To achieve this, strategies for humanrobot interaction are needed that are adapted to operators' needs and characteristics in an industrial context, i.e., Operator 5.0. This paper presents a research design for the development of a framework for human-robot interaction strategies based on ANEMONE, which is an evaluation framework based on activity theory, the seven stages of action model, and user experience (UX) evaluation methodology. At two companies, ANEMONE is applied in two concrete use cases, collaborative kitting and mobile robot platforms for chemical laboratory assignments. The proposed research approach consists of 1) evaluations of existing demonstrators, 2) development of preliminary strategies that are implemented, 3) re-evaluations and 4) cross-analysis of results to produce an interaction strategy framework. The theoretically and empirically underpinned framework-to-be is expected to, in the long run, contribute to a sustainable work environment for Operator 5.0.

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  • 16.
    Allalou, Amin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Methods for 2D and 3D Quantitative Microscopy of Biological Samples2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    New microscopy techniques are continuously developed, resulting in more rapid acquisition of large amounts of data. Manual analysis of such data is extremely time-consuming and many features are difficult to quantify without the aid of a computer. But with automated image analysis biologists can extract quantitative measurements and increases throughput significantly, which becomes particularly important in high-throughput screening (HTS). This thesis addresses automation of traditional analysis of cell data as well as automation of both image capture and analysis in zebrafish high-throughput screening. 

    It is common in microscopy images to stain the nuclei in the cells, and to label the DNA and proteins in different ways. Padlock-probing and proximity ligation are highly specific detection methods that  produce point-like signals within the cells. Accurate signal detection and segmentation is often a key step in analysis of these types of images. Cells in a sample will always show some degree of variation in DNA and protein expression and to quantify these variations each cell has to be analyzed individually. This thesis presents development and evaluation of single cell analysis on a range of different types of image data. In addition, we present a novel method for signal detection in three dimensions. 

    HTS systems often use a combination of microscopy and image analysis to analyze cell-based samples. However, many diseases and biological pathways can be better studied in whole animals, particularly those that involve organ systems and multi-cellular interactions. The zebrafish is a widely-used vertebrate model of human organ function and development. Our collaborators have developed a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae. This thesis presents improvements to the system, including accurate positioning of the fish which incorporates methods for detecting regions of interest, making the system fully automatic. Furthermore, the thesis describes a novel high-throughput tomography system for screening live zebrafish in both fluorescence and bright field microscopy. This 3D imaging approach combined with automatic quantification of morphological changes enables previously intractable high-throughput screening of vertebrate model organisms.

    List of papers
    1. A detailed analysis of 3D subcellular signal localization
    Open this publication in new window or tab >>A detailed analysis of 3D subcellular signal localization
    Show others...
    2009 (English)In: Cytometry Part A, ISSN 1552-4922, Vol. 75A, no 4, p. 319-328Article in journal (Refereed) Published
    Abstract [en]

    Detection and localization of fluorescent signals in relation to other subcellular structures is an important task in various biological studies. Many methods for analysis of fluorescence microscopy image data are limited to 2D. As cells are in fact 3D structures, there is a growing need for robust methods for analysis of 3D data. This article presents an approach for detecting point-like fluorescent signals and analyzing their subnuclear position. Cell nuclei are delineated using marker-controlled (seeded) 3D watershed segmentation. User-defined object and background seeds are given as input, and gradient information defines merging and splitting criteria. Point-like signals are detected using a modified stable wave detector and localized in relation to the nuclear membrane using distance shells. The method was applied to a set of biological data studying the localization of Smad2-Smad4 protein complexes in relation to the nuclear membrane. Smad complexes appear as early as 1 min after stimulation while the highest signal concentration is observed 45 min after stimulation, followed by a concentration decrease. The robust 3D signal detection and concentration measures obtained using the proposed method agree with previous observations while also revealing new information regarding the complex formation.

    Keywords
    3D image analysis, fluorescence signal segmentation, subcellular positioning, Smad detection
    National Category
    Computer and Information Sciences
    Identifiers
    urn:nbn:se:uu:diva-98014 (URN)10.1002/cyto.a.20663 (DOI)000264513800006 ()
    Available from: 2009-02-05 Created: 2009-02-05 Last updated: 2018-01-13Bibliographically approved
    2. Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis
    Open this publication in new window or tab >>Single-cell A3243G mitochondrial DNA mutation load assays for segregation analysis
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    2007 (English)In: Journal of Histochemistry and Cytochemistry, ISSN 0022-1554, E-ISSN 1551-5044, Vol. 55, no 11, p. 1159-1166Article in journal (Refereed) Published
    Abstract [en]

    Segregation of mitochondrial DNA (mtDNA) is an important underlying pathogenic factor in mtDNA mutation accumulation in mitochondrial diseases and aging, but the molecular mechanisms of mtDNA segregation are elusive. Lack of high-throughput single-cell mutation load assays lies at the root of the paucity of studies in which, at the single-cell level, mitotic mtDNA segregation patterns have been analyzed. Here we describe development of a novel fluorescence-based, non-gel PCR restriction fragment length polymorphism method for single-cell A3243G mtDNA mutation load measurement. Results correlated very well with a quantitative in situ Padlock/rolling circle amplification–based genotyping method. In view of the throughput and accuracy of both methods for single-cell A3243G mtDNA mutation load determination, we conclude that they are well suited for segregation analysis.

    Keywords
    A3243G mtDNA, Aging, Heteroplasmy, Mitochondrial diseases, Mutation load, Padlock probing, PCR-RFLP, Segregation
    National Category
    Medical and Health Sciences
    Identifiers
    urn:nbn:se:uu:diva-12658 (URN)10.1369/jhc.7A7282.2007 (DOI)000250320100009 ()17679731 (PubMedID)
    Available from: 2008-01-09 Created: 2008-01-09 Last updated: 2022-01-28Bibliographically approved
    3. BlobFinder, a tool for fluorescence microscopy image cytometry
    Open this publication in new window or tab >>BlobFinder, a tool for fluorescence microscopy image cytometry
    2009 (English)In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 94, no 1, p. 58-65Article in journal (Refereed) Published
    Abstract [en]

    Images can be acquired at high rates with modern fluorescence microscopy hardware, giving rise to a demand for high-speed analysis of image data. Digital image cytometry, i.e., automated measurements and extraction of quantitative data from images of cells, provides valuable information for many types of biomedical analysis. There exists a number of different image analysis software packages that can be programmed to perform a wide array of useful measurements. However, the multi-application capability often compromises the simplicity of the tool. Also, the gain in speed of analysis is often compromised by time spent learning complicated software. We provide a free software called BlobFinder that is intended for a limited type of application, making it easy to use, easy to learn and optimized for its particular task. BlobFinder can perform batch processing of image data and quantify as well as localize cells and point like source signals in fluorescence microscopy images, e.g., from FISH, in situ PLA and padlock probing, in a fast and easy way.

    Keywords
    Image cytometry, Single cell analysis, FISH, Software
    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Research subject
    Computerized Image Analysis
    Identifiers
    urn:nbn:se:uu:diva-87971 (URN)10.1016/j.cmpb.2008.08.006 (DOI)000264282400006 ()18950895 (PubMedID)
    Available from: 2009-01-22 Created: 2009-01-16 Last updated: 2018-06-26Bibliographically approved
    4. Robust signal detection in 3D fluorescence microscopy
    Open this publication in new window or tab >>Robust signal detection in 3D fluorescence microscopy
    2010 (English)In: Cytometry. Part A, ISSN 1552-4922, Vol. 77A, no 1, p. 86-96Article in journal (Refereed) Published
    Abstract [en]

    Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to Visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.

    National Category
    Bioinformatics and Systems Biology
    Identifiers
    urn:nbn:se:uu:diva-98015 (URN)10.1002/cyto.a.20795 (DOI)000273384700011 ()
    Available from: 2009-02-05 Created: 2009-02-05 Last updated: 2022-01-28Bibliographically approved
    5. High-throughput in vivo optical projection tomography of small vertebrates
    Open this publication in new window or tab >>High-throughput in vivo optical projection tomography of small vertebrates
    Show others...
    (English)Manuscript (preprint) (Other academic)
    National Category
    Natural Sciences
    Identifiers
    urn:nbn:se:uu:diva-159203 (URN)
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2011-11-04
    6. Fully automated cellular-resolution vertebrate screening platform with parallel animal processing
    Open this publication in new window or tab >>Fully automated cellular-resolution vertebrate screening platform with parallel animal processing
    Show others...
    2012 (English)In: Lab on a Chip, ISSN 1473-0197, E-ISSN 1473-0189, Vol. 12, no 4, p. 711-716Article in journal (Refereed) Published
    Abstract [en]

    The zebrafish larva is an optically-transparent vertebrate model with complex organs that is widelyused to study genetics, developmental biology, and to model various human diseases. In this article, wepresent a set of novel technologies that significantly increase the throughput and capabilities of ourpreviously described vertebrate automated screening technology (VAST). We developed a robustmulti-thread system that can simultaneously process multiple animals. System throughput is limitedonly by the image acquisition speed rather than by the fluidic or mechanical processes. We developedimage recognition algorithms that fully automate manipulation of animals, including orienting andpositioning regions of interest within the microscope’s field of view. We also identified the optimalcapillary materials for high-resolution, distortion-free, low-background imaging of zebrafish larvae.

    National Category
    Computer Vision and Robotics (Autonomous Systems)
    Identifiers
    urn:nbn:se:uu:diva-159202 (URN)10.1039/c1lc20849g (DOI)000299380800007 ()
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2018-01-12Bibliographically approved
    7. Image based measurements of single cell mtDNA mutation load MTD 2007
    Open this publication in new window or tab >>Image based measurements of single cell mtDNA mutation load MTD 2007
    Show others...
    2007 (English)In: Medicinteknikdagarna 2007, 2007Conference paper, Published paper (Other (popular science, discussion, etc.))
    Abstract [en]

    Cell cultures as well as cells in tissue always display a certain degree of variability,and measurements based on cell averages will miss important information contained in a heterogeneous population. These differences among cells in a population may be essential to quantify when looking at, e.g., protein expression and mutations in tumor cells which often show high degree of heterogeneity.

    Single nucleotide mutations in the mithochondrial DNA (mtDNA) can accumulate and later be present in large proportions of the mithocondria causing devastating diseases. To study mtDNA accumulation and segregation one needs to measure the amount of mtDNA mutations in each cell in multiple serial cell culture passages. The different degrees of mutation in a cell culture can be quantified by making measurements on individual cells as an alternative to looking at an average of a population. Fluorescence microscopy in combination with automated digital image analysis provides an efficient approach to this type of single cell analysis.

    Image analysis software for these types of applications are often complicated and not easy to use for persons lacking extensive knowledge in image analysis, e.g., laboratory personnel. This paper presents a user friendly implementation of an automated method for image based measurements of mtDNA mutations in individual cells detected with padlock probes and rolling-circle amplification (RCA). The mitochondria are present in the cell’s cytoplasm, and here each cytoplasm has to be delineated without the presence of a cytoplasmic stain. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.

    National Category
    Other Computer and Information Science
    Identifiers
    urn:nbn:se:uu:diva-12745 (URN)
    Available from: 2008-01-11 Created: 2008-01-11 Last updated: 2018-01-12Bibliographically approved
    8. Increasing the dynamic range of in situ PLA
    Open this publication in new window or tab >>Increasing the dynamic range of in situ PLA
    Show others...
    2011 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 8, no 11, p. 892-893Article in journal, Editorial material (Refereed) Published
    National Category
    Biological Sciences
    Identifiers
    urn:nbn:se:uu:diva-159199 (URN)10.1038/nmeth.1743 (DOI)000296891800004 ()
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2022-01-28Bibliographically approved
    9. High-throughput cellular-resolution in vivo vertebrate screening
    Open this publication in new window or tab >>High-throughput cellular-resolution in vivo vertebrate screening
    Show others...
    2011 (English)In: Proc. 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, 2011Conference paper, Published paper (Refereed)
    National Category
    Medical Image Processing
    Identifiers
    urn:nbn:se:uu:diva-159201 (URN)
    Available from: 2011-09-25 Created: 2011-09-25 Last updated: 2011-11-04
    Download full text (pdf)
    fulltext
  • 17.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Curic, Vladimir
    Pardo-Martin, Carlos
    Massachusetts Institute of Technology, USA.
    Yanik, Mehmet Fatih
    Massachusetts Institute of Technology, USA.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Approaches for increasing throughput andinformation content of image-based zebrafishscreens2011In: Proceeding of SSBA 2011, 2011Conference paper (Other academic)
    Abstract [en]

    Microscopy in combination with image analysis has emerged as one of the most powerful and informativeways to analyze cell-based high-throughput screening (HTS) samples in experiments designed to uncover novel drugs and drug targets. However, many diseases and biological pathways can be better studied in whole animals, particularly diseases and pathways that involve organ systems and multicellular interactions, such as organ development, neuronal degeneration and regeneration, cancer metastasis, infectious disease progression and pathogenesis. The zebrafish is a wide-spread and popular vertebrate model of human organfunction and development, and it is unique in the sense that large-scale in vivo genetic and chemical studies are feasible due in part to its small size, optical transparency,and aquatic habitat. To improve the throughput and complexity of zebrafish screens, a high-throughput platform for cellular-resolution in vivo chemical and genetic screens on zebrafish larvae has been developed at Yanik lab at Research Laboratory of Electronics, MIT, USA. The system loads live zebrafish from reservoirs or multiwell plates, positions and rotates them for high-speed confocal imaging of organs,and dispenses the animals without damage. We present two improvements to the described system, including automation of positioning of the animals and a novel approach for brightfield microscopy tomographic imaging of living animals.

  • 18.
    Allalou, Amin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wu, Yuelong
    Ghannad-Rezaie, Mostafa
    Eimon, Peter M.
    Yanik, Mehmet Fatih
    Automated deep-phenotyping of the vertebrate brain2017In: eLIFE, E-ISSN 2050-084X, Vol. 6, article id e23379Article in journal (Refereed)
  • 19. Alves-Oliveira, Patricia
    et al.
    Sequeira, Pedro
    Melo, Francisco S.
    Castellano, Ginevra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Paiva, Ana
    Empathic robot for group learning: A field study2019In: ACM Transactions on Human-Robot Interaction, E-ISSN 2573-9522, Vol. 8, no 1, article id 3Article in journal (Refereed)
  • 20.
    Andersson, Arne W.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sandblad, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Tschirner, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Recognizing complexity: Visualization for skilled professionals in complex work situations2013In: Building Bridges: HCI, Visualization, and Cognitive Ergonomics, Springer Berlin/Heidelberg, 2013Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 21.
    Andersson, Arne W
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sandblad, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Tschirner, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Recognizing complexity: Visualization for skilled professionals in complex work situations2014In: Building Bridges: HCI, Visualization, and Non-formal Modeling / [ed] Achim Ebert, Gerrit C. van den Veer, Gitta Domik, Nahum D. Gershon, & Inga Scheler, Heidelberg: Springer Berlin/Heidelberg, 2014, p. 47-66Chapter in book (Refereed)
  • 22.
    Andersson, Arne W
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sandblad, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Tschirner, Simon
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Framtida tågtrafikstyrning: Sammanfattande forskningsrapport. Slutrapport från FOT-projektet2015Report (Other academic)
  • 23.
    Andersson, Axel
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    An Analytical Neighborhood Enrichment Score for Spatial OmicsManuscript (preprint) (Other academic)
    Abstract [en]

    The neighborhood enrichment test is commonly used to quantify spatial enrichment or depletion between spatial points with categorical labels — a data type frequently occurring in spatial omics. Traditionally, it is performed via permutation-based Monte Carlo methods, which can be computationally expensive. This study presents an analytical solution to the neighborhood enrichment problem. This direct calculation strongly correlated with traditional tests, offering substantially faster processing times across eight spatial omics datasets. Further validation on an extensive Xenium dataset highlighted the method’s ability to rapidly analyze large-scale data, making it a valuable tool for advancing spatial omics research. The implementation is publicly available.

  • 24.
    Andersson, Axel
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Behanova, Andrea
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Avenel, Christophe
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Windhager, Jonas
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Points2Regions: Fast, interactive clustering of imaging-based spatial transcriptomics dataManuscript (preprint) (Other academic)
    Abstract [en]

    Imaging-based spatial transcriptomics techniques generate image data that, once processed, results in a set of spatial points with categorical labels for different mRNA species. A crucial part of analyzing downstream data involves the analysis of these point patterns. Here, biologically interesting patterns can be explored at different spatial scales. Molecular patterns on a cellular level would correspond to cell types, whereas patterns on a millimeter scale would correspond to tissue-level structures. Often, clustering methods are employed to identify and segment regions with distinct point-patterns. Traditional clustering techniques for such data are constrained by reliance on complementary data or extensive machine learning, limiting their applicability to tasks on a particular scale. This paper introduces 'Points2Regions', a practical tool for clustering spatial points with categorical labels. Its flexible and computationally efficient clustering approach enables pattern discovery across multiple scales, making it a powerful tool for exploratory analysis. Points2Regions has demonstrated efficient performance in various datasets, adeptly defining biologically relevant regions similar to those found by scale-specific methods. As a Python package integrated into TissUUmaps and a Napari plugin, it offers interactive clustering and visualization, significantly enhancing user experience in data exploration. In essence, Points2Regions presents a user-friendly and simple tool for exploratory analysis of spatial points with categorical labels. 

  • 25.
    Andersson, Axel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Behanova, Andrea
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Cell Segmentation of in situ Transcriptomics Data using Signed Graph Partitioning2023In: Graph-Based Representations in Pattern Recognition / [ed] Mario Vento; Pasquale Foggia; Donatello Conte; Vincenzo Carletti, Cham: Springer, 2023, p. 139-148Conference paper (Refereed)
    Abstract [en]

    The locations of different mRNA molecules can be revealed by multiplexed in situ RNA detection. By assigning detected mRNA molecules to individual cells, it is possible to identify many different cell types in parallel. This in turn enables investigation of the spatial cellular architecture in tissue, which is crucial for furthering our understanding of biological processes and diseases. However, cell typing typically depends on the segmentation of cell nuclei, which is often done based on images of a DNA stain, such as DAPI. Limiting cell definition to a nuclear stain makes it fundamentally difficult to determine accurate cell borders, and thereby also difficult to assign mRNA molecules to the correct cell. As such, we have developed a computational tool that segments cells solely based on the local composition of mRNA molecules. First, a small neural network is trained to compute attractive and repulsive edges between pairs of mRNA molecules. The signed graph is then partitioned by a mutex watershed into components corresponding to different cells. We evaluated our method on two publicly available datasets and compared it against the current state-of-the-art and older baselines. We conclude that combining neural networks with combinatorial optimization is a promising approach for cell segmentation of in situ transcriptomics data. The tool is open-source and publicly available for use at https://github.com/wahlby-lab/IS3G.

  • 26.
    Andersson, Axel
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Diego, Ferran
    HCI/IWR and Department of Physics and Astronomy, Heidelberg University, Heidelberg.
    Hamprecht, Fred A.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. HCI/IWR and Department of Physics and Astronomy, Heidelberg University, Heidelberg.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    ISTDECO: In Situ Transcriptomics Decoding by DeconvolutionManuscript (preprint) (Other academic)
    Abstract [en]

    In Situ Transcriptomics (IST) is a set of image-based transcriptomics approaches that enables localisation of gene expression directly in tissue samples. IST techniques produce multiplexed image series in which fluorescent spots are either present or absent across imaging rounds and colour channels. A spot’spresence and absence form a type of barcoded pattern that labels a particular type of mRNA. Therefore, the expression of agene can be determined by localising the fluorescent spots and decode the barcode that they form. Existing IST algorithms usually do this in two separate steps: spot localisation and barcode decoding. Although these algorithms are efficient, they are limited by strictly separating the localisation and decoding steps. This limitation becomes apparent in regions with low signal-to-noise ratio or high spot densities. We argue that an improved gene expression decoding can be obtained by combining these two steps into a single algorithm. This allows for an efficient decoding that is less sensitive to noise and optical crowding. We present IST Decoding by Deconvolution (ISTDECO), a principled decoding approach combining spectral and spatial deconvolution into a single algorithm. We evaluate ISTDECOon simulated data, as well as on two real IST datasets, and compare with state-of-the-art. ISTDECO achieves state-of-the-art performance despite high spot densities and low signal-to-noise ratios. It is easily implemented and runs efficiently using a GPU.ISTDECO implementation, datasets and demos are available online at: github.com/axanderssonuu/istdeco

  • 27.
    Andersson, Axel
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Escriva Conde, Maria
    Stockholm University.
    Surova, Olga
    Stockholm University.
    Vermeulen, Peter
    GZA Hospital Sint-Augustinus.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Nilsson, Mats
    Stockholm University.
    Nyström, Hanna
    Umeå University.
    Spatial transcriptome mapping of the desmoplastic growth pattern of colorectal liver metastases by in situ sequencing reveals a biologically relevant zonation of the desmoplastic rimManuscript (preprint) (Other academic)
  • 28.
    Andersson, Axel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Koriakina, Nadezhda
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Sladoje, Nataša
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division Vi3.
    End-to-end Multiple Instance Learning with Gradient Accumulation2022In: 2022 IEEE International Conference on Big Data (Big Data), Institute of Electrical and Electronics Engineers (IEEE), 2022, p. 2742-2746Conference paper (Refereed)
    Abstract [en]

    Being able to learn on weakly labeled data and provide interpretability are two of the main reasons why attention-based deep multiple instance learning (ABMIL) methods have become particularly popular for classification of histopathological images. Such image data usually come in the form of gigapixel-sized whole-slide-images (WSI) that are cropped into smaller patches (instances). However, the sheer volume of the data poses a practical big data challenge: All the instances from one WSI cannot fit the GPU memory of conventional deep-learning models. Existing solutions compromise training by relying on pre-trained models, strategic selection of instances, sub-sampling, or self-supervised pre-training. We propose a training strategy based on gradient accumulation that enables direct end-to-end training of ABMIL models without being limited by GPU memory. We conduct experiments on both QMNIST and Imagenette to investigate the performance and training time and compare with the conventional memory-expensive baseline as well as a recent sampled-based approach. This memory-efficient approach, although slower, reaches performance indistinguishable from the memory-expensive baseline.

  • 29.
    Andersson, Axel
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Partel, Gabriele
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Solorzano, Leslie
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wählby, Carolina
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Transcriptome-Supervised Classification of Tissue Morphology Using Deep Learning2020In: IEEE 17th International Symposium on Biomedical Imaging (ISBI), 2020, p. 1630-1633Conference paper (Refereed)
    Abstract [en]

    Deep learning has proven to successfully learn variations in tissue and cell morphology. Training of such models typically relies on expensive manual annotations. Here we conjecture that spatially resolved gene expression, e.i., the transcriptome, can be used as an alternative to manual annotations. In particular, we trained five convolutional neural networks with patches of different size extracted from locations defined by spatially resolved gene expression. The network is trained to classify tissue morphology related to two different genes, general tissue, as well as background, on an image of fluorescence stained nuclei in a mouse brain coronal section. Performance is evaluated on an independent tissue section from a different mouse brain, reaching an average Dice score of 0.51. Results may indicate that novel techniques for spatially resolved transcriptomics together with deep learning may provide a unique and unbiased way to find genotype phenotype relationships

  • 30.
    Andersson, Robin
    et al.
    Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Berglund, Jonas
    Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Coşkun, Aykut
    KUAR, Media and Visual Arts Department, Koç University, Istanbul, Turkey.
    Fjeld, Morten
    Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden.
    Obaid, Mohammad
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Defining gestural interactions for large vertical touch displays2017In: Human-Computer Interaction – INTERACT 2017, Springer, 2017, p. 36-55Conference paper (Refereed)
    Abstract [en]

    As new technologies emerge, so do new ways of interacting with the digital domain. In this paper, the touch interaction paradigm is challenged for use on large touch displays of 65 in. in size. We present a gesture elicitation study with 26 participants carried out on twelve actions commonly used on touch displays. The results and analysis of 312 touch gestures revealed agreement rates for each action. We report several findings including the results of a set of ten unique (and a few secondary) gestures, a taxonomy classifying the defined gestures, a pilot study on the defined gestures, and explicit design implications. We discuss the results and include several important factors for future considerations. We aim at helping future designers and engineers to design interactions for large touch displays

  • 31.
    Andreasson, Rebecca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. School of Informatics, University of Skövde, Skövde, Sweden.
    Alenljung, Beatrice
    School of Informatics, University of Skövde, Skövde, Sweden.
    Billing, Erik
    School of Informatics, University of Skövde, Skövde, Sweden.
    Lowe, Robert
    Department of Applied ITUniversity of Gothenburg, Gothenburg, Sweden.
    Affective touch in human–robot interaction: Conveying emotion to the Nao robot2018In: International Journal of Social Robotics, ISSN 1875-4791, E-ISSN 1875-4805, Vol. 10, p. 473-491Article in journal (Refereed)
    Abstract [en]

    Affective touch has a fundamental role in human development, social bonding, and for providing emotional support in interpersonal relationships. We present, what is to our knowledge, the first HRI study of tactile conveyance of both positive and negative emotions (affective touch) on the Nao robot, and based on an experimental set-up from a study of human–human tactile communication. In the present work, participants conveyed eight emotions to a small humanoid robot via touch. We found that female participants conveyed emotions for a longer time, using more varied interaction and touching more regions on the robot’s body, compared to male participants. Several differences between emotions were found such that emotions could be classified by the valence of the emotion conveyed, by combining touch amount and duration. Overall, these results show high agreement with those reported for human–human affective tactile communication and could also have impact on the design and placement of tactile sensors on humanoid robots.

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  • 32.
    Andreasson, Rebecca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Arweström Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Towards a distributed cognition perspective of the Swedish train traffic system2017In: Proceedings of the 13th SweCog Conference, Högskolan i Skövde , 2017, p. 37-39Conference paper (Refereed)
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    fulltext
  • 33.
    Andreasson, Rebecca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Jansson, Anders A
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lindblom, Jessica
    Past and future challenges for railway research and the role of a systems perspective2019In: Proc. 20th Congress of the International Ergonomics Association: Volume VII, Springer, 2019, p. 1737-1746Conference paper (Refereed)
    Abstract [en]

    Operational train traffic is dependent on an efficient traffic plan monitored and executed by the traffic controllers, the proficient maneuvering of the trains by the train drivers, and on the interaction, communication, and coordination between these two work roles. The railway research community, and the branch of industry itself, has called for an integrated systems perspective for the whole train traffic system to achieve an efficient performance. As human-human and human-technology interactions are natural parts of the socio-technical system of train traffic, the aim of this paper is to provide illustrative examples for why a systems perspective is needed for the future of railway research. Furthermore, we present the theoretical framework of distributed cognition (DCog) as a necessary addition to the theoretical and methodological toolbox of the Human Factors and Ergonomics (HF&E) discipline. To realize efficient and coordinated processes involved in organizing and executing operational train traffic, the paper proposes that the DCog framework should be implemented in the train traffic domain as a viable approach forward.

  • 34.
    Andreasson, Rebecca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Lindblom, Jessica
    Högskolan i Skövde, Institutionen för informationsteknologi.
    The coordination between train traffic controllers and train drivers: a distributed cognition perspective on railway2019In: Cognition, Technology & Work, ISSN 1435-5558, E-ISSN 1435-5566, Vol. 21, no 3, p. 417-443Article in journal (Refereed)
    Abstract [en]

    Although there has long been a call for a holistic systems perspective to better understand real work in the complex domain of railway traffic, prior research has not strongly emphasised the socio-technical perspective. In operational railway traffic, the successful planning and execution of the traffic are the product of the socio-technical system comprised by both train drivers and traffic controllers. This paper presents a study inspired by cognitive ethnography with the aim to characterise the coordinating activities that are conducted by train traffic controllers and train drivers in the work practices of the socio-technical system of Swedish railway. The theoretical framework of distributed cognition (DCog) is used as a conceptual and analytical tool to make sense of the complex railway domain and the best practices as they are developed and performed “in the wild”. The analysis reveals a pattern of collaboration and coordination of actions among the workers and we introduce the concept of enacted actionable practices as a key concern for understanding how a successfully executed railway traffic emerges as a property of the socio-technical system. The implications for future railway research are briefly discussed.

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  • 35.
    Andreasson, Rebecca
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Högskolan i Skövde, Institutionen för informationsteknologi.
    Lindblom, Jessica
    Högskolan i Skövde, Institutionen för informationsteknologi.
    Thorvald, Peter
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Tool use and collaborative work of dock assembly in practice2017In: Production & Manufacturing Research, ISSN 2169-3277, Vol. 5, no 1, p. 164-190Article in journal (Refereed)
    Abstract [en]

    In order to deepen the understanding of the intrinsic interactions and interplay between humans, tools, and environment from a systems perspective, research in the wild (RITW) approaches have gained traction during recent decades as they provide a higher ecological validity of findings. This paper presents a RITW study, investigating how assembly, in this case dock assembly of forwarders, was done in practice. As our theoretical foundation, we used the framework of distributed cognition, which is one of the main pillars of RITW. The findings are presented in narrative form, describing and highlighting that the workers achieve an efficient production outcome by being integral parts of the whole production process and doing so through coordination of activities benefitting the shared goal of the distributed socio-technical system.

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  • 36. Andrée, Martin
    et al.
    Paasch, Jesper M.
    Paulsson, Jenny
    Seipel, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    BIM and 3D property visualisation2018In: Proc. FIG Congress 2018, 2018, article id 9367Conference paper (Refereed)
  • 37.
    Anklin, Valentin
    et al.
    IBM Research-Europe, Zurich, Switzerland;ETH Zurich, Zurich, Switzerland.
    Pati, Pushpak
    IBM Research-Europe, Zurich, Switzerland;ETH Zurich, Zurich, Switzerland.
    Jaume, Guillaume
    IBM Research-Europe, Zurich, Switzerland;EPFL, Lausanne, Switzerland.
    Bozorgtabar, Behzad
    EPFL, Lausanne, Switzerland.
    Foncubierta-Rodriguez, Antonio
    IBM Research-Europe, Zurich, Switzerland.
    Thiran, Jean-Philippe
    EPFL, Lausanne, Switzerland.
    Sibony, Mathilde
    Cochin Hospital, Paris, France;University of Paris, Paris, France.
    Gabrani, Maria
    IBM Research-Europe, Zurich, Switzerland.
    Goksel, Orcun
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. ETH Zurich, Zurich, Switzerland.
    Learning Whole-Slide Segmentation from Inexact and Incomplete Labels Using Tissue Graphs2021In: Medical Image Computing and Computer Assisted Intervention: MICCAI 2021, Cham: Springer Nature, 2021, p. 636-646Conference paper (Refereed)
    Abstract [en]

    Segmenting histology images into diagnostically relevant regions is imperative to support timely and reliable decisions by pathologists. To this end, computer-aided techniques have been proposed to delineate relevant regions in scanned histology slides. However, the techniques necessitate task-specific large datasets of annotated pixels, which is tedious, time-consuming, expensive, and infeasible to acquire for many histology tasks. Thus, weakly-supervised semantic segmentation techniques are proposed to leverage weak supervision which is cheaper and quicker to acquire. In this paper, we propose SEGGINI, a weakly-supervised segmentation method using graphs, that can utilize weak multiplex annotations, i.e., inexact and incomplete annotations, to segment arbitrary and large images, scaling from tissue microarray (TMA) to whole slide image (WSI). Formally, SEGGINI constructs a tissue-graph representation for an input image, where the graph nodes depict tissue regions. Then, it performs weakly-supervised segmentation via node classification by using inexact image-level labels, incomplete scribbles, or both. We evaluated SEGGINI on two public prostate cancer datasets containing TMAs and WSIs. Our method achieved state-of-the-art segmentation performance on both datasets for various annotation settings while being comparable to a pathologist baseline. Code and models are available at: https://github.com/histocartography/seg-gini

  • 38.
    Arnold, Hannah
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Panara, Virginia
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Palaeobiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Gorniok, Beata Filipek
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Skoczylas, Renae
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Ranefall, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Gloger, Marleen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Hogan, Benjamin M.
    Koltowska, Katarzyna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Mafba and  Mafbb Differentially Regulate Lymphatic Endothelial Cell Migration in Topographically Distinct Manners2021In: SSRN Electronic Journal, E-ISSN 1556-5068Article in journal (Refereed)
    Abstract [en]

    Lymphangiogenesis is the formation of lymphatic vessels from pre-existing vessels, a dynamic process that requires cell migration. Regardless of location, lymphatic endothelial cell (LEC) progenitors probe their surroundings while migrating to form the lymphatic network. Lymphatic development regulation depends on the transcription factor MAFB in different species. Zebrafish Mafba, expressed in LEC progenitors, is essential for their migration in the trunk. However, the transcriptional mechanism that orchestrate LEC migration in different lymphatic endothelial beds remains elusive. Here, we uncover topographically different requirements of the two paralogues, Mafba and Mafbb, for lymphatic cell migration. Both mafba and mafbb are necessary for facial lymphatic development, but mafbb is dispensable for trunk lymphatic development. On the molecular level, we demonstrate a regulatory network where Vegfc-Vegfd-SoxF-Mafba-Mafbb are essential in the facial lymphangiogenesis. We identify that mafba and mafbb fine-tune the directionality of LEC migration and vessel morphogenesis that is ultimately necessary for lymphatic function. 

  • 39.
    Arnold, Hannah
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Panara, Virginia
    Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Palaeobiology. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Hussmann, Melina
    WWU Munster, Med Fac, Inst Cardiovasc Organogenesis & Regenerat, Munster, Germany..
    Gorniok, Beata Filipek
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology.
    Skoczylas, Renae
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Ranefall, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Gloger, Marleen
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Vascular Biology.
    Allalou, Amin
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Hogan, Benjamin M.
    Univ Melbourne, Dept Anat & Physiol, Melbourne, Vic 3000, Australia.;Univ Melbourne, Sir Peter MacCallum Dept Oncol, Melbourne, Vic 3000, Australia.;Peter MacCallum Canc Ctr, Organogenesis & Canc Program, Melbourne, Vic 3000, Australia..
    Schulte-Merker, Stefan
    WWU Munster, Med Fac, Inst Cardiovasc Organogenesis & Regenerat, Munster, Germany..
    Koltowska, Katarzyna
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology.
    mafba and mafbb differentially regulate lymphatic endothelial cell migration in topographically distinct manners2022In: Cell Reports, E-ISSN 2211-1247, Vol. 39, no 12, article id 110982Article in journal (Refereed)
    Abstract [en]

    Lymphangiogenesis, formation of lymphatic vessels from pre-existing vessels, is a dynamic process that requires cell migration. Regardless of location, migrating lymphatic endothelial cell (LEC) progenitors probe their surroundings to form the lymphatic network. Lymphatic-development regulation requires the transcription factor MAFB in different species. Zebrafish Mafba, expressed in LEC progenitors, is essential for their migration in the trunk. However, the transcriptional mechanism that orchestrates LEC migration in different lymphatic endothelial beds remains elusive. Here, we uncover topographically different requirements of the two paralogs, Mafba and Mafbb, for LEC migration. Both mafba and mafbb are necessary for facial lymphatic development, but mafbb is dispensable for trunk lymphatic development. On the molecular level, we demonstrate a regulatory network where Vegfc-Vegfd-SoxF-Mafba-Mafbb is essential in facial lymphangiogenesis. We identify that mafba and mafbb tune the directionality of LEC migration and vessel morphogenesis that is ultimately necessary for lymphatic function.

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  • 40. Arvidsson, Anna
    et al.
    Sarve, Hamid
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Johansson, Carina B.
    Comparing and visualizing titanium implant integration in rat bone using 2D and 3D techniques2015In: Journal of Biomedical Materials Research. Part B - Applied biomaterials, ISSN 1552-4973, E-ISSN 1552-4981, Vol. 103, no 1, p. 12-20Article in journal (Refereed)
    Abstract [en]

    The aim was to compare the osseointegration of grit-blasted implants with and without a hydrogen fluoride treatment in rat tibia and femur, and to visualize bone formation using state-of-the-art 3D visualization techniques. Grit-blasted implants were inserted in femur and tibia of 10 Sprague-Dawley rats (4 implants/rat). Four weeks after insertion, bone implant samples were retrieved. Selected samples were imaged in 3D using Synchrotron Radiation-based CT (SRCT). The 3D data was quantified and visualized using two novel visualization techniques, thread fly-through and 2D unfolding. All samples were processed to cut and ground sections and 2D histomorphometrical comparisons of bone implant contact (BIC), bone area (BA), and mirror image area (MI) were performed. BA values were statistically significantly higher for test implants than controls (p<0.05), but BIC and MI data did not differ significantly. Thus, the results partly indicate improved bone formation at blasted and hydrogen fluoride treated implants, compared to blasted implants. The 3D analysis was a valuable complement to 2D analysis, facilitating improved visualization. However, further studies are required to evaluate aspects of 3D quantitative techniques, with relation to light microscopy that traditionally is used for osseointegration studies. (c) 2014 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 103B: 12-20, 2015.

  • 41.
    Arweström Jansson, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Vad är det trafikledarna gör som automationen inte klarar?: Tågtrafikstyrning med människan i centrum2017Report (Other (popular science, discussion, etc.))
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  • 42.
    Arweström Jansson, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Axelsson, AntonUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.Andreasson, RebeccaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.Billing, ErikUniversity of Skövde.
    Proceedings of the 13th SweCog Conference2017Conference proceedings (editor) (Refereed)
  • 43.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Between Insanity and Love2015In: Computers & Society: The Newsletter of the ACM Special Interest Group on Computers and Society Special Issue on 20 Years of ETHICOMP / [ed] Mark Coeckelbergh, Bernd Stahl, and Catherine Flick, 2015, p. 154-158Conference paper (Refereed)
    Abstract [en]

    Technology has opened up more opportunities to find bet- ter partners, especially via online dating sites . In addition, technology related to love and sex currently goes far beyond online dating sites. Technology influences our intimate life more and more. Media started to pick up romantic rela- tionship between human beings and digital characters of- ten. Furthermore, today, many wearable devices to experi- ence virtual sex have come into the market. And also robots designed for having a sex with human beings are being de- veloped rapidly. Some might claim having a sex without love or without reproduction is just totally pointless. Or, having a sex with robots is totally “insane”. But apparently there are big market needs, and modern technology seems to be able to satisfy them. This paper explores how it is possible for us to feeling love or sexual desire for non-organic objects by conducting the interview survey, and also considers why people want to have technology for satisfying sexual desire from a philosophical perspective. 

  • 44.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Designing "Open Education": How does the ICT-based system function as a new medium of participation for sustainability?2013In: The possibilities of ethical ICT, Kolding: University of Southern Denmark , 2013, p. 33-36Conference paper (Refereed)
    Abstract [en]

    Information and communication technology (ICT) has developed and deployed rapidly since 1980’s. Until now ICT has been considered as one of the most important infrastructures in living in the present globalized society. Along with diffusion of personal computers and highly leveraging information on the web, the way of learning has been changing gradually. Hundreds universities, institutes and companies constructs and releases the “open education” platform based on ICT, for example iTunes U, TakingITGlobal and so on. These open education platforms are basically open for everyone who wants to learn by using contents on the website for free in so far as they can access the Internet. And the movement toward the construction and use of ICT-based education platform is supported by international organizations, such as the Centre for Educational Research and Innovation (CERI) in OECD and UNESCO’s project “the Virtual University and e-learning”.

  • 45.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Globalization and the change of employment system2011In: Management systems / [ed] Japanese Association of Management Systems, Tokyo: Nippon Hyoronsha , 2011Chapter in book (Refereed)
  • 46.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    ICT professionalism and gender2011In: Management quality science / [ed] Hiroshi Yamashita, Tokyo: Chuokeizaisha , 2011, p. 181-184Chapter in book (Refereed)
  • 47.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    New form of social ties through communicating in social media (Sosharu media ga tukuru atarashii kizuna no katachi)2012In: Information and Management  64th Conferenceedings Spring / [ed] Japan Society for Information and Management, 2012, p. 141-144Conference paper (Refereed)
  • 48.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Research in Computer/Information Ethics: A Gender Gap Analysis and Consequences2013In: Ambiguous Technologies: Philosophical Issues, Practical Solutions, Human Nature, Lisbon: Universidade Autonoma de Lisboa , 2013Conference paper (Refereed)
    Abstract [en]

    Technology democratization enforces a never-ending process of risk/responsibility harmonization through with ethical assumptions. However, it is crucial to debate the gender gap within our community (reasons) and explore the potential “outcome” of female contribution. This panel does not promote a direct hit with the sessions, although the intention is to be controversial and influencer concerning a latent problem inside our community. 

  • 49.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Rethinking ICT's contribution to sustainability and education2012In: New technologies, education for sustainable development and critical pedagogy / [ed] Vassilios Makrakis and Nelly Kostoulas-Makrakis, Rethymnon, Greece: ICTeESD, University of Crete , 2012, p. 232-235Chapter in book (Refereed)
    Abstract [en]

    The open education system based on Information and communication technology (ICT) can provide great opportunities for people to learn regardless of resident area, language, gender, age and so on. Currently people use it actively and build up new social networks as learning communities or study groups on the Internet. Shared knowledge and the process of sharing knowledge established through online communication are considered as key elements in the context of strengthen the individual and the country. In other words, creating the open education platform and content plays a role of designing a culture and society. However, it is not easy to realize the ideal concept of “open education” because people have many differences in language, culture, political system, ideology, thought, deployment of ICT et cetera. In order to create the open education system, which has a high degree of usability and effectiveness, we need to closely examine social roles and difficulties of the ICT-based education system in designing sustainable societies. And also the ICT-based educational system is established through the continuous human-computer interaction. Therefore, all participants get involved with developing the open education and each of them assumes a responsibility for making the open educational contents more abundant.

  • 50.
    Asai, Ryoko
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Social Influence on Cooperation and Coordination2013In: ICT-ethics: Sweden and Japan, Linköping: LiU Tryck , 2013, p. 24-30Chapter in book (Refereed)
    Abstract [en]

    Information and Communication Technology (ICT) creates novel products and services and promotes innovation in the whole of global society, and the amount of data, which we can gather and use, or even just see, is increasing dramatically. Searching and checking information on the Internet is our ordinary way of doing, people enjoy online shopping commonly and sometime look for their partners through the Internet. Internet, mobile networks and social media have flourished greatly in our daily lives, ICT has developed and deployed very dynamic and diverse as well. Particulary our communication patterns are greatly affected by permeation of social media into our daily life.

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