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  • 51.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Borgefors., G.
    Bylund, A.-C.
    Lindgård, A.
    Lundström, K.
    Rakotonirainy, O.
    Soussi, B.
    A Segmentation Technique to Determine Fat Content in NMR Images of Beef Meat2002In: IEEE Transactions on Nuclear Science, Vol. 49, no 1, p. 195-199Article in journal (Refereed)
    Abstract [en]

    The world of meat faces a permanent need for new methods of meat

  • 52.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Borgefors, G.
    Bylund, A.-C.
    Lindgård, A.
    Lundström, K.
    Rakotonirainy, O.
    Soussi, B.
    Testing MRI and image analysis techniques for fat quantification in meat science2000Conference paper (Refereed)
    Abstract [en]

    The world of meat faces a permanent need for new methods of meat quality

  • 53.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Högberg, A.
    Lundström, K.
    Borgefors, G.
    Colour Image Analysis Technique for Measuring of Fat in Meat: An Application forthe Meat Industry2001Conference paper (Refereed)
    Abstract [en]

    Intramuscular fat content in meat influences some important meat quality

  • 54.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Piazza, E.
    A picture of doctoral studies in Italy2001In: Eurodoc 2001, European Conference of Doctoral Students, Uppsala, Sweden, 2001Conference paper (Other scientific)
  • 55.
    Ballerini, L.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Piazza, E.
    The future of Italian doctors2002In: Eurodoc 2002, European Conference of Doctoral Students, Girona, Spain, 2002Conference paper (Other scientific)
  • 56.
    Barnden, L
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Kwiatek, R
    Lau, Y
    Hutton, B
    Thurfjell, L
    Pile, K
    Rowe, C
    Validation of fully automatic brain SPET to MR co-registration2000In: EUROPEAN JOURNAL OF NUCLEAR MEDICINE, ISSN 0340-6997, Vol. 27, no 2, p. 147-154Article in journal (Refereed)
    Abstract [en]

    Fully automatic co-registration of functional to anatomical brain images using information intrinsic to the scans has been validated in a clinical setting for positron emission tomography (PET), but not for single-photon emission tomography (SPET). In thi

  • 57.
    Barrera Tony, Hast Anders, Bengtsson Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A fast all-integer ellipse discretization algorithm2003In: Graphics Programming Methods, 2003, p. 121-131Chapter in book (Refereed)
  • 58.
    Barrera Tony, Hast Anders, Bengtsson Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A fast and simple all-integer parametric line2003Chapter in book (Refereed)
  • 59. Barrera, Tony
    et al.
    Hast, Anders
    Creative Media Lab, University of Gävle.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    An alternative model for shading of diffuse light for rough materials2008In: Game Programming Gems 7 / [ed] Scott Jacobs, Boston: Charles River Media , 2008, 1, p. 373-380Chapter in book (Other academic)
  • 60.
    Barrera Tony, Hast Anders, Bengtsson Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Faster Shading by Equal Angle Interpolation of Vectors2004In: IEEE Transactions on Visualization and Computer Graphics, Vol. 10, no 2, p. 217-223Article in journal (Refereed)
  • 61.
    Barrera, Tony
    et al.
    Barrera-Kristiansen AB.
    Hast, Anders
    University of Gävle.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Minimal Acceleration Hermite Curves2005In: Game Programming Gems 5, Charles River Media, Hingham, Massachusetts , 2005, p. 225-231Chapter in book (Refereed)
    Abstract [en]

    This gem shows how a curve with minimal acceleration can be obtained using Hermite splines [Hearn04]. Acceleration is higher in the bends and therefore this type of curve is a minimal bending curve. This type of curve can be useful for subdivision surfaces when it is required that the surface has this property, which assures that the surface is as smooth as possible. A similar approach for Bézier curves and subdivision can be found in [Overveld97]. It could also be very useful for camera movements [Vlachos01] since it allows that both the position and the direction of the camera can be set for the curve. Moreover, we show how several such curves can be connected in order to achieve continuity between the curve segments.

  • 62.
    Barrera Tony, Hast Anders, Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Surface Construction with Near Least Square Acceleration based on Vertex Normals on Triangular Meshes2002In: Proceedings from Sigrad 2002, 2002, p. 17-22Conference paper (Other scientific)
  • 63. Barrera, Tony
    et al.
    Hast, Anders
    Creative Media Lab, University of Gävle.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Trigonometric splines2008In: Game programming Gems 7 / [ed] Scott Jacobs, Boston: Charles River Media , 2008, 1, p. 191-198Chapter in book (Other (popular science, discussion, etc.))
  • 64.
    Bax, Gerhard
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Environment and Landscape Dynamics. ELD.
    Remote sensing and 3D visualization of geological structures in mountain ranges:: examples from the Northern Scandinavian Caledonides and the south Tibetan Himalayas2004In: The 26th Nordic Geological Winter Meeting: Abstract volume, 2004, p. 105-Conference paper (Refereed)
  • 65.
    Bax, Gerhard
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Earth Sciences, Department of Earth Sciences, Environment and Landscape Dynamics. ELD.
    Buchroithner, ManfredDepartment of Cartography.
    Proceedings of the 5th International Symposium of the use of Remote Sensing in Maountain Cartography: High-Mountain Remote Sensing Cartography 19982002Conference proceedings (editor) (Refereed)
  • 66.
    Bengtsson, E.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    The technical development in the ICT-field2000In: IT at school between vision and practice - a research overview, 2000, p. 39-55Chapter in book (Other scientific)
  • 67.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Analysis of 3D images of molecules, cells, tissues and organs2007In: Medicinteknikdagarna 2007, 2007, p. 1-Conference paper (Other scientific)
    Abstract [en]

    Our world is three dimensional. With our eyes we mainly see the surfaces of 3D objects and in conventional imaging we see projections of parts of the 3D world down to 2D. But over the last decades new imaging techniques such as tomography and confocal microscopy have evolved that make true 3D volume images available,. These images can reveal information about the inner properties and conditions of objects, e.g. our bodies, that can be of immense value to science and medicine. But to really explore the information in these images we need computer support.

    At the Centre for Image Analysis in Uppsala we are developing methods for the analysis and visualisation of volume images. A nice aspect of image processing methods is that they in most cases are independent of the scale in the images. In this presentation we will give examples of how images of widely different scales can be analysed and visualised.

    - At the highest resolution we have images of protein molecules created by cryo-electron tomography with voxels of a few nanometers.

    - Using confocal microscopy we can also image single molecules, but then only seeing them as bright spots that need to be localized at micrometer scales in the cells.

    - The cells build up tissue and using conventional pathology stains or micro CT we can image the tissue in 2D and 3D. We are using such images to develop methods for studying tissue integration of implants.

    - Finally conventional X-ray tomography and magnetic resonance tomography provide images on the organ level with voxels in the millimetre range. We are developing methods for liver segmentation in CT data and visualising the contrast uptake over time in MR angiography images of breasts.

  • 68.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Computerized Cell Image Analysis: Past, Present and Future2003Conference paper (Refereed)
  • 69.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Computerized Cell Image Processing in Healthcare2005In: Proceedings of Healthcomm2005, 2005, p. 11-17Conference paper (Refereed)
    Abstract [en]

    The visual interpretation of images is at the core of most medical diagnostic procedures and the final decision for many diseases, including cancer, is based on microscopic examination of cells and tissues. Through screening of cell samples the incidence and mortality of cervical cancer have been reduced significantly. The visual interpretation is, however, tedious and in many cases error-prone. Therefore many attempts have been made at using the computer to supplement or replace the human visual inspection by computer analysis and to automate some of the more tedious visual screening tasks. The computers and computer networks have also been used to manage, store, transmit and display images of cells and tissues making it possible to visually analyze cells from remote locations. In this presentation these developments are traced from their very beginning through the present situation and into the future.

  • 70.
    Bengtsson, Ewert
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Recognizing signs of malignancy: The quest for computer assisted cancer screening and diagnosis systems2010In: International Conference on Computational Intelligence and Computing Research (ICCIC), 2010 IEEE, Coimbatore, India: IEEE Digital Library , 2010, p. 1-6Conference paper (Refereed)
    Abstract [en]

    Almost all cancers are diagnosed through visual examination of microscopic tissue samples. Visual screening of cell samples, so called PAP-smears, has drastically reduced the incidence of cervical cancers in countries that have implemented population wide screening programs. But the visual examination is tedious, subjective and expensive. There has therefore been much research aiming for computer assisted or automated cell image analysis systems for cancer detection and diagnosis. Progress has been made but still most of cytology and pathology is done visually. In this presentation I will discuss some of the major issues involved, examine some of the proposed solutions and give some comments about the state of the art.

  • 71.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Curic, VladimirUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Nyström, IngelaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Strand, RobinUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Wadelius, LenaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Wernersson, ErikUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Centre for Image Analysis Annual Report 20092010Collection (editor) (Other academic)
  • 72.
    Bengtsson, Ewert
    et al.
    Uppsala University.
    Dahlqvist, Bengt
    Uppsala University.
    Eriksson, Olle
    Uppsala University.
    Nordin, Bo
    Uppsala University.
    Jarkrans, Torsten
    Uppsala University.
    Stenkvist, Björn
    Computer-assisted Scanning Microscopy in Cytology1982In: Proceedings of the IEEE International Symposium on Medical Imaging and Image Interpretation, 1982, p. 497-503Conference paper (Refereed)
  • 73.
    Bengtsson, Ewert
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Norell, KristinUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Nyström, IngelaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Wadelius, LenaUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.Wernersson, ErikUppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Annual Report 20082009Collection (editor) (Other academic)
  • 74.
    Bengtsson, Ewert
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Rodenacker, Karsten
    A feature set for cytometry on digitized microscopic images2003In: Analytical Cellular Pathology, Vol. 24, no 1, p. 1-36Article in journal (Refereed)
  • 75.
    Bengtsson, Ewert
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Wählby, Carolina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lindblad, Joakim
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Robust cell image segmentation methods.2004In: Pattern Recognition and Image Analysis: Advances in Mathematical Theory and Applications, ISSN 1054-6618, Vol. 14, no 2, p. 157-167Article in journal (Refereed)
    Abstract [en]

    Biomedical cell image analysis is one of the main application fields of computerized image analysis. This paper outlines the field and the different analysis steps related to it. Relative advantages of different approaches to the crucial step of image segmentation are discussed. Cell image segmentation can be seen as a modeling problem where different approaches are more or less explicitly based on cell models. For example, thresholding methods can be seen as being based on a model stating that cells have an intensity that is different from the surroundings. More robust segmentation can be obtained if a combination of features, such as intensity, edge gradients, and cellular shape, is used. The seeded watershed transform is proposed as the most useful tool for incorporating such features into the cell model. These concepts are illustrated by three real-world problems.

  • 76.
    Bengtsson Ewert, Wählby Carolina, Lindblad Joakim
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Robust Cell Image Segmentation Methods2003Conference paper (Refereed)
  • 77.
    Bergholm, Fredrik
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    The Plenoscope Concept and Image Formation2002In: Proceedings of SSAB 2002, 2002, p. 75-78Conference paper (Other scientific)
  • 78. Bernander, Karl B.
    et al.
    Gustavsson, Kenneth
    Selig, Bettina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Sintorn, Ida-Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Improving the stochastic watershed2013In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 34, no 9, p. 993-1000Article in journal (Refereed)
    Abstract [en]

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

  • 79. Bi, Yin
    et al.
    Lv, Mingsong
    Wei, Yangjie
    Guan, Nan
    Yi, Wang
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computer Systems.
    Multi-feature fusion for thermal face recognition2016In: Infrared physics & technology, ISSN 1350-4495, E-ISSN 1879-0275, Vol. 77, p. 366-374Article in journal (Refereed)
  • 80.
    Björk, Ingrid
    et al.
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology.
    Kavathatzopoulos, Iordanis
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Robots, ethics and language2015In: Computers & Society: The Newsletter of the ACM Special Interest Group on Computers and Society Special Issue on 20 Years of ETHICOMP / [ed] Mark Coeckelbergh, Bernd Stahl, and Catherine Flick; Vaibhav Garg and Dee Weikle, ACM Digital Library, 2015, p. 268-273Conference paper (Refereed)
    Abstract [en]

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

  • 81.
    Blomgren, Bo
    Uppsala University, Medicinska vetenskapsområdet, Faculty of Medicine, Department of Women's and Children's Health.
    Morphometrical Methodology in Quantification of Biological Tissue Components2004Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Objective:

    To develop and validate computer-assisted morphometrical methods, based on stereological theory, in order to facilitate the analysis and quantitative measurements of biological tissue components.

    Material and methods:

    Biopsy specimens from the vaginal wall or from the vestibulum vaginae of healthy women, or from women suffering from incontinence or vestibulitis were used.

    A number of histochemical methods for light microscopy were used, and modified for the different morphometrical analyses. Electron microscopy was used to reveal collagen fibre diameter.

    Computer-assisted morphometry, based on image analysis and stereology, was employed to analyse the different tissue components in the biopsies. Computer programs for these purposes were developed and validated.

    Results:

    The results show that computer-assisted morphometry is of great value for quantitative measurements of the following tissue components:

    Epithelium: The epithelial structure, instead of just thickness, was measured in an unbiased way.

    Collagen: The collagen fibril diameter was determined in electron microscopic specimens, and the collagen content was analysed in light microscopic specimens.

    Elastic fibres: The amount of elastic fibres in the connective tissue was measured after visualisation by autofluorescence.

    Vasculature: A stereological method using a cycloid grid was implemented in a computer program. Healthy subjects were compared with patients suffering from vestibulitis. The results were identical in the two groups.

    Smooth muscle: A stereological method using a point grid was implemented in a computer program. Using the Delesse principle, the fibres were calculated as area fractions. The area fractions were highly variable among the different specimens.

    Conclusion:

    Morphometry, used correctly, is an important analysis method in histopathological research. It is important that the methods are as simple and user-friendly as possible. The present studies show that this methodology can be applied for most quantitative histological analyses.

    List of papers
    1. Different organization of collagen fibrils in stress-incontinent women of fertile age
    Open this publication in new window or tab >>Different organization of collagen fibrils in stress-incontinent women of fertile age
    Show others...
    1998 In: Acta Obstetrica et Gynecologica Scandinavica, ISSN 0001-6349, Vol. 77, p. 87-94Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-92277 (URN)
    Available from: 2004-10-28 Created: 2004-10-28Bibliographically approved
    2. A computerised stereological method for quantitative estimation of surface area of blood vessels
    Open this publication in new window or tab >>A computerised stereological method for quantitative estimation of surface area of blood vessels
    2001 In: Image Analysis and Stereology, ISSN 1560-3139, Vol. 20, p. 129-132Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-92278 (URN)
    Available from: 2004-10-28 Created: 2004-10-28Bibliographically approved
    3. A novel method for visualisation of elastic fibres - suitable for image analysis and morphometry
    Open this publication in new window or tab >>A novel method for visualisation of elastic fibres - suitable for image analysis and morphometry
    Show others...
    2001 In: Image analysis and stereology, ISSN 1560-3139, Vol. 20, p. 522-526Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-92279 (URN)
    Available from: 2004-10-28 Created: 2004-10-28Bibliographically approved
    4. A computerised, unbiased method for epithelial measurement
    Open this publication in new window or tab >>A computerised, unbiased method for epithelial measurement
    Show others...
    2004 In: Micron, Vol. 35, p. 319-329Article in journal (Refereed) Published
    Identifiers
    urn:nbn:se:uu:diva-92280 (URN)
    Available from: 2004-10-28 Created: 2004-10-28Bibliographically approved
    5. The structure of the normal vaginal wall as revealed by morphometry
    Open this publication in new window or tab >>The structure of the normal vaginal wall as revealed by morphometry
    Article in journal (Refereed) Submitted
    Identifiers
    urn:nbn:se:uu:diva-92281 (URN)
    Available from: 2004-10-28 Created: 2004-10-28Bibliographically approved
  • 82.
    Bolin, Karl
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Helgesson, Johan
    Automatic image analysis of concrete cracks2003Report (Other scientific)
    Abstract [en]

    The objective of the work is to investigate if image analysis methods

  • 83.
    Borgefors, G.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Some weighted distance transforms in four dimensions2000Conference paper (Refereed)
    Abstract [en]

    In a digital distance transform, each picture element in the shape (background)

  • 84.
    Borgefors, G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, I.
    Sanniti di Baja, G.
    Svensson, S.
    Simplification of 3D skeletons using distance information2000Conference paper (Refereed)
    Abstract [en]

    We present a method to simplify the structure of the surface skeleton of a 3D

  • 85.
    Borgefors, G.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ramella, G.
    Sanniti di Baja, G.
    Hierarchical Decomposition of Multi-Scale Skeletons2001In: IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 23, no 11, p. 1296-1312Article in journal (Refereed)
    Abstract [en]

    This paper presents a new procedure to hierarchically decompose a multi-scale discrete skeleton. The

  • 86.
    Borgefors, G
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ramella, G
    Sanniti, di Baja G
    Shape and topology preserving multi-valued image pyramids for multi-resolution skeletonization2001In: PATTERN RECOGNITION LETTERS, ISSN 0167-8655, Vol. 22, no 6-7, p. 741-751Article in journal (Refereed)
    Abstract [en]

    Starting from a binary digital image, a multi-valued pyramid is built and suitably treated, so that shape and topology properties of the pattern are preserved satisfactorily at all resolution levels. The multi-valued pyramid can then be used as input data

  • 87.
    Borgefors, G.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, S.
    Optimal Local Distances for Distance Transforms in 3D using an ExtendedNeighbourhood2001Conference paper (Refereed)
    Abstract [en]

    Digital distance transforms are useful tools for many image analysis tasks. In the

  • 88.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Kedjekod - ett sätt att beskriva former i digitala bilder2005In: Problemlösning är # 1, Liber, Stockholm , 2005, p. 38-42Chapter in book (Other scientific)
  • 89.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Räta linjer på dataskärmen: En illustration av rekursivitet2008In: Nämnaren, ISSN 0348-2723, Vol. 35, no 1, p. 46-50Article in journal (Other (popular science, discussion, etc.))
  • 90.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Tessellationer i matematik, arkitektur och konst2004In: Matenmatikbiennalen 2004: Malmö, 22-24 jan. 2004, 2004, p. 4-Conference paper (Other (popular scientific, debate etc.))
  • 91.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Tessellationer: konsten att dela upp planet i regelbundna mönster2008In: Människor och matematik: Läsebok för nyfikna, Göteborg: NCM , 2008, p. 185-210Chapter in book (Other (popular science, discussion, etc.))
  • 92.
    Borgefors, Gunilla
    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.
    The Scarcity of Universal Colour Names2018In: Proceedings of 7th International Conference on Pattern Recognition Applications and Methods / [ed] Maria de Marisco, Gabriella Sannniti di Baja, Ana Fred, 2018, p. 496-502Conference paper (Refereed)
    Abstract [en]

    There is a trend in Computer Vision to use over twenty colour names for image annotation, retrieval and to train deep learning networks to name unknown colours for human use. This paper will show that there is little consistency of colour naming between languages and even between individuals speaking the same language. Experiments will be cited that show that your mother tongue influences how your brain processes colour. It will also be pointed out that the eleven so called basic colours in English are not universal and cannot be applied to other languages. The conclusion is that only the six Hering primary colours, possibly with simple qualifications, are the only ones you should use if you aim for universal usage of your systems. That is: black, white, red, green, blue, and yellow.

  • 93.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Weighted digital distance transforms in four dimensions2003In: Discrete Applied Mathematics, Vol. 125, p. 161-176Article in journal (Refereed)
    Abstract [en]

    A digital distance transformation converts a binary image in Z^n to a distance transform, where each picture element in the foreground (background) has a value measuring the closest distance to the background (foreground). In a weighted distance transform

  • 94.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Weighted distance transforms in four dimensions2003In: Discrete Applied Mathematics, Vol. 125, p. 161-176Article in journal (Refereed)
    Abstract [en]

    A digital distance transformation converts a binary image in Z^n to a distance transform, where each picture element in the foreground (background) has a value measuring the closest distance to the background (foreground). In a weighted distance transform

  • 95.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Sanniti di Baja, Gabriella
    Institute of Cybernetics ``E. Caianiello," C.N.R., Pozzuoli, Naples,.
    Discrete Skeletons from Distance Transforms in 2D and 3D2008In: Medial Representations: Mathematics, Algorithms and Applications, Netherlands: Springer Verlag , 2008, p. 155-190Chapter in book (Other academic)
    Abstract [en]

    We present discrete methods to compute the digital skeleton of shapes in 2D and 3D images. In 2D, the skeleton is a set of curves, while in 3D it will be a set of surfaces and curves, the surface skeleton, or a set of curves, the curve skeleton. A general scheme could, in principle, be followed for both 2D and 3D discrete skeletonization. However, we will describe one approach for 2D skeletonization, mainly based on marking in the distance transform the shape elements that should be assigned to the skeleton, and another approach for 3D skeletonization, mainly based on iterated element removal. In both cases, the distance transform of the image will play a key role to obtain skeletons reflecting important shape features such as symmetry, elongation, and width.

  • 96.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    An Approximation of the Maximal Inscribed Convex Set of a Digital Obj2005In: In F. Roli and S. Vitulano, editors, Proceedings of 13th International Conference on Image Analysis and Processing (ICIAP'05), 2005, p. 438-445Conference paper (Refereed)
    Abstract [en]

    In several application projects we have discovered the need of computing the maximal inscribed convex set of a digital shape. Here we present an algorithm for computing a reasonable approximation of this set, that can be used in both 2D and 3D. The main idea is to iteratively identify the deepest concavity and then remove it by cutting off as little as possible of the shape. We show results using both synthetic and real examples.

  • 97.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    On Maximal Balls in Three Volume Grids2009In: PRIP'2009: Pattern Recognition and Information Processing, Minsk, Belarus, Minsk: Publishing Center of BSU , 2009, p. 31-36Conference paper (Refereed)
    Abstract [en]

    A volume image can be digitized in different grids, not only the cubic one. The fcc and bcc grids have many advantages, as they are more dense than the cubic one. The set of maximal balls in a shape in a volume image is a compact but complete description of the shape. The original set, identified by rules dependent on the metric used, can be further reduced, by observing that some balls are covered by groups of other balls. The set of maximal balls can, for example, be used for compression, manipulation and as anchor points for topologically correct medial representations.

  • 98.
    Borgefors, Gunilla
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, Stina
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fuzzy border distance transforms and their use in 2D skeletonization2002Conference paper (Refereed)
    Abstract [en]

    Segmentation is always a difficult task in image analysis. In this paper,

  • 99. Borodulina, Svetlana
    et al.
    Wernersson, Erik L. G.
    Kulachenko, Artem
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Extracting fiber and network connectivity data using microtomography images of paper2016In: Nordic Pulp & Paper Research Journal, ISSN 0283-2631, E-ISSN 2000-0669, Vol. 31, no 3, p. 469-478Article in journal (Refereed)
  • 100.
    Brandtberg, T.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Individual tree-based timber volume assessment using high spatial resolution laserscanning data2000In: Symposium on Image Analysis - SSAB 2000, 2000, p. 83-86Conference paper (Other scientific)
1234567 51 - 100 of 557
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