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  • 1.
    Axelsson, Maria
    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.
    Chinga, Gary
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Nygård, Per
    Malmberg, Filip
    Solheim, Olav
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Detailed quantification of the 3D structure of newsprints in X-ray synchrotron radiation microtomography images2006In: Progress in Paper Physics Seminar, Oxford, Ohio, 2006, 2006Conference paper (Other academic)
  • 2.
    Axelsson, Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Sintorn, Ida-Maria
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, Stina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Individual pore segmentation in 3D volumes of fibrous materials2005In: SSBA Symposium on Image Analysis 2005, 2005Conference paper (Other scientific)
  • 3.
    Axelsson, Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Svensson, Stina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis.
    2D Ring Artifact Reduction of X-ray Tomography Images2007In: Proceedings SSBA 2007: Symposium on Image Analysis, Linköping, March 14-15, 2007Conference paper (Other scientific)
  • 4.
    Axelsson, Maria
    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.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Reduction of Ring Artifacts in High Resolution X-Ray Microtomography Images2006In: Pattern Recognition: 28th DAGM Symposium, Berlin, Germany, September 2006, Proceedings, 2006, p. 61-70Conference paper (Refereed)
    Abstract [en]

    Ring artifacts can occur in reconstructed images from X-ray microtomography as full or partial circles centred on the rotation axis. In this paper, a 2D method is proposed that reduces these ring artifacts in the reconstructed images. The method consists of two main parts. First, the artifacts are localised in the image using local orientation estimation of the image structures and filtering to find ring patterns in the orientation information. Second, the map of the located artifacts is used to calculate a correction image using normalised convolution. The method is evaluated on 2D images from volume data of paper fibre imaged at the European Synchrotron Radiation Facility (ESRF) with high resolution X-ray microtomography. The results show that the proposed method reduces the artifacts and restores the pixel values for all types of partial and complete ring artifacts where the signal is not completely saturated.

  • 5. Ballerini, Lucia
    et al.
    Franke-Stenport, Victoria
    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.
    Johansson, Carina B.
    Comparison of histomorphometrical data obtained with two different image analysis methods2007In: Journal of materials science. Materials in medicine, ISSN 0957-4530, E-ISSN 1573-4838, Vol. 18, no 8, p. 1471-1479Article in journal (Refereed)
    Abstract [en]

    A common way to determine tissue acceptance of biomaterials is to perform histomorphometrical analysis on histologically stained sections from retrieved samples with surrounding tissue, using various methods. The "time and money consuming" methods and techniques used are often "in house standards". We address light microscopic investigations of bone tissue reactions on un-decalcified cut and ground sections of threaded implants. In order to screen sections and generate results faster, the aim of this pilot project was to compare results generated with the in-house standard visual image analysis tool (i.e., quantifications and judgements done by the naked eye) with a custom made automatic image analysis program. The histomorphometrical bone area measurements revealed no significant differences between the methods but the results of the bony contacts varied significantly. The raw results were in relative agreement, i.e., the values from the two methods were proportional to each other: low bony contact values in the visual method corresponded to low values with the automatic method. With similar resolution images and further improvements of the automatic method this difference should become insignificant. A great advantage using the new automatic image analysis method is that it is time saving-analysis time can be significantly reduced.

  • 6. Bogren, Karin
    et al.
    Gamstedt, Kristofer
    Berthold, Fredrik
    Lindström, Mikael
    Nygård, Per
    Malmberg, Filip
    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.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Axelsson, Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Stress transfer and failure in pulpfibre reinforced composites: Effects of microstructure characterized by Xray microtomography2006In: 2006 Progress in Paper Physics: A seminar, 2006Conference paper (Other academic)
  • 7.
    Borgefors (editor), 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.
    Short Descriptions of International Journals on Image Processing and its Applications2012Report (Other academic)
  • 8.
    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

  • 9.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Hemmafrun som lyckades2007In: Nämnaren, ISSN 0348-2723, Vol. 34, no 1, p. 18-20Article in journal (Other (popular science, discussion, etc.))
  • 10.
    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)
  • 11.
    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.))
  • 12.
    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.))
  • 13.
    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 (ICPRAM 2018) / [ed] Maria de Marisco, Gabriella Sannniti di Baja, Ana Fred, SciTePress, 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.

  • 14.
    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
    Discrete Skeletons from Distance Transforms in 2D and 3D2005Report (Other (popular science, discussion, etc.))
  • 15.
    Borgefors, Gunilla
    et al.
    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.
    Nyström, Ingela
    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.
    Sintorn, Ida-Maria
    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.
    Strand, Robin
    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.
    Wadelius, Lena
    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.
    Centre for Image Analysis Annual Report 20032004Report (Other (popular scientific, debate etc.))
  • 16.
    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.

  • 17.
    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,

  • 18.
    Curic, Vladimir
    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.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Faculty of Engineering, University of Novi Sad, Serbia.
    Sladoje, Natasa
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. University of Novi Sad, Serbia.
    Sarve, Hamid
    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.
    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.
    A new set distance and its application to shape registration2014In: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 17, no 1, p. 141-152Article in journal (Refereed)
  • 19.
    Curic, Vladimir
    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 of Visual Information and 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.
    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.
    Salience adaptive structuring elements2012In: IEEE Journal on Selected Topics in Signal Processing, ISSN 1932-4553, E-ISSN 1941-0484, Vol. 6, no 7, p. 809-819Article in journal (Refereed)
    Abstract [en]

    Spatially adaptive structuring elements adjust their shape to the local structures in the image, and are often defined by a ball in a geodesic distance or gray-weighted distance metric space. This paper introduces salience adaptive structuring elements as spatially variant structuring elements that modify not only their shape, but also their size according to the salience of the edges in the image. Morphological operators with salience adaptive structuring elements shift edges with high salience to a less extent than those with low salience. Salience adaptive structuring elements are less flexible than morphological amoebas and their shape is less affected by noise in the image. Consequently, morphological operators using salience adaptive structuring elements have better properties.

  • 20.
    Fouard, Céline
    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. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    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.
    Weighted distance transforms generalized to modules and their computation on point lattices2007In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 40, no 9, p. 2453-2474Article in journal (Refereed)
    Abstract [en]

    This paper presents the generalization of weighted distances to modules and their computation through the chamfer algorithm on general point lattices. The first part is dedicated to formalization of definitions and properties (distance, metric, norm) of weighted distances on modules. It resumes tools found in literature to express the weighted distance of any point of a module and to compute optimal weights in the general case to get rotation invariant distances. The second part of this paper proves that, for any point lattice, the sequential two-scan chamfer algorithm produces correct distance maps. Finally, the definitions and computation of weighted distances are applied to the face-centered cubic (FCC) and body-centered cubic (BCC) grids.

  • 21.
    Höglund, Anna-Stina
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Liu, Jingxia
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Karlsson, Patrick
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Lindblad, Joakim
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bengtsson, Ewert
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Larsson, Lars
    The spatial distribution of nuclei in single skeletal muscle cells as visualised by 3-D images:: the differences in organisation between species and between healthy cells and cells affected by disease2007In: Biophysical Journal: 637A-637A Suppl. S, 2007Conference paper (Other scientific)
  • 22.
    Kylberg, Gustaf
    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.
    Uppström, Mats
    Hedlund, Kjell-Olof
    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.
    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.
    Segmentation of virus particle candidates in transmission electron microscopy images2012In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 245, no 2, p. 140-147Article in journal (Refereed)
    Abstract [en]

    In this paper, we present an automatic segmentation method that detects virus particles of various shapes in transmission electron microscopy images. The method is based on a statistical analysis of local neighbourhoods of all the pixels in the image followed by an object width discrimination and finally, for elongated objects, a border refinement step. It requires only one input parameter, the approximate width of the virus particles searched for. The proposed method is evaluated on a large number of viruses. It successfully segments viruses regardless of shape, from polyhedral to highly pleomorphic.

  • 23. Linh, Troung Kieu
    et al.
    Imiya, Atsushi
    Strand, Robin
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Supercover of Non-square and Non-cubic Grids2004In: Proc. 10th International Workshop on Combinatorial Image Analysis (IWCIA 2004): Auckland, New Zealand, Dec. 2004, 2004, p. 88-97Conference paper (Refereed)
    Abstract [en]

    We define algebraic discrete geometry of hexagonal- and rhombic-dodecahedral- grids on a plane in a space, respectively. Since, a hexagon and a rhombic-dodecahedron are elements for tilling on a plane and in a space, respectively, a hexagon and a rhombic-dodecahedron are suitable as elements of discrete objects on a plane and in a space, respectively. For the description of linear objects in a discrete space, algebraic discrete geometry provides a unified treatment employing double Diophantus equations. In this paper, we introduce supercove for the hexagonal- and rhombic-dodecahedral- grid-systems on a plane and in a space, respectively.

  • 24. Nygård, Per
    et al.
    Gradin, Per
    Gregersen, Øyvind
    Lindblad, Joakim
    Axelsson, Maria
    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.
    Svensson, Stina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Damage Mechanisms in Paper2006In: 2006 Progress in Paper Physics, 2006Conference paper (Other academic)
  • 25.
    Nyström, Ingela
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Sanniti di Baja, Gabriella
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    2D grey-level convex hull computation: a discrete 3D approach2003Conference paper (Refereed)
    Abstract [en]

    We compute discrete convex hulls in 2D grey-level images, where we interpret grey-level values as heights in 3D landscapes. For these 3D objects, using a 3D binary method, we compute approximations of their convex hulls. Differently from other grey-level

  • 26.
    Saha, Punam K.
    et al.
    Univ Iowa, Dept Elect & Comp Engn, Iowa City, IA 52242 USA.; Univ Iowa, Dept Radiol, Iowa City, IA 52242 USA.
    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.
    Sanniti di Baja, Gabriella
    CNR, Inst Cybernet E Caianiello, I-80078 Naples, Italy.; CNR, Inst High Performance Comp & Networking, I-80131 Naples, Italy.
    A survey on skeletonization algorithms and their applications2016In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 76, p. 3-12Article in journal (Refereed)
    Abstract [en]

    Skeletonization provides an effective and compact representation of objects, which is useful for object description, retrieval, manipulation, matching, registration, tracking, recognition, and compression. It also facilitates efficient assessment of local object properties, e.g., scale, orientation, topology, etc. Several computational approaches are available in literature toward extracting the skeleton of an object, some of which are widely different in terms of their principles. In this paper, we present a comprehensive and concise survey of different skeletonization algorithms and discuss their principles, challenges, and benefits. Topology preservation, parallelization, and multi-scale skeletonization approaches are discussed. Finally, various applications of skeletonization are reviewed and the fundamental challenges of assessing the performance of different skeletonization algorithms are discussed.

  • 27. Saha, Punam K.
    et al.
    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.
    Sanniti di Baja, Gabriella
    Skeletonization and its applications – a review2017In: Skeletonization: Theory, Methods, and Applications, London: Academic Press, 2017, p. 3-42Chapter in book (Refereed)
  • 28. Saha, Punam K.
    et al.
    Borgefors, GunillaUppsala 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.Sanniti di Baja, Gabriella
    Skeletonization: Theory, Methods, and Applications2017Collection (editor) (Refereed)
  • 29. Saha, Punam K.
    et al.
    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.
    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.
    Digital topology and geometry in medical image processing: A survey2015In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 34, no 9, p. 1940-1964Article in journal (Refereed)
    Abstract [en]

    Digital topology and geometry refers to the use of topologic and geometric properties and features for images defined in digital grids. Such methods have been widely used in many medical imaging applications, including image segmentation, visualization, manipulation, interpolation, registration, surface-tracking, object representation, correction, quantitative morphometry etc. Digital topology and geometry play important roles in medical imaging research by enriching the scope of target outcomes and by adding strong theoretical foundations with enhanced stability, fidelity, and efficiency. This paper presents a comprehensive yet compact survey on results, principles, and insights of methods related to digital topology and geometry with strong emphasis on understanding their roles in various medical imaging applications. Specifically, this paper reviews methods related to distance analysis and path propagation, connectivity, surface-tracking, image segmentation, boundary and centerline detection, topology preservation and local topological properties, skeletonization, and object representation, correction, and quantitative morphometry. A common thread among the topics reviewed in this paper is that their theory and algorithms use the principle of digital path connectivity, path propagation, and neighborhood analysis. 

  • 30.
    Sanniti di Baja, Gabriella
    et al.
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Interfaculty Units, Centre for Image Analysis. Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Discrete 3D tools applied to 2D grey-level images2005In: Image Analysis and Processing - ICIAP 2005: 13th International Conference, 2005, p. 229-236Conference paper (Refereed)
    Abstract [en]

    2D grey-level images are interpreted as 3D binary images, where the grey-level plays the role of the third coordinate. In this way, algorithms devised for 3D binary images can be used to analyse 2D grey-level images. Here, we present three such algorithms. The first algorithm smoothes a 2D grey-level image by flattening its geometrical and grey-level peaks while simultaneously filling in geometrical and grey-level valleys, regarded as non significant in the problem domain. The second algorithm computes an approximation of the convex hull of a 2D grey-level object, by building a covering polyhedron closely fitting the corresponding object in a 3D binary image. The result obtained is convex both from the geometrical point of view and as concerns grey-levels. The third algorithm skeletonizes a 2D grey-level object by skeletonizing the top surface of the object in the corresponding 3D binary image.

  • 31.
    Sarve, Hamid
    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.
    Friberg, Bertil
    Brånemark Clinic.
    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.
    Johansson, Carina B.
    University of Gothenburg, Department of Prosthodontics/Dental Materials Science, Institute of Odontology.
    Introducing a novel analysis technique for osseointegrated dental implants retrieved 29 years postsurgery2013In: Clinical Implant Dentistry and Related Research, ISSN 1523-0899, E-ISSN 1708-8208, Vol. 15, no 4, p. 538-549Article in journal (Refereed)
    Abstract [en]

    Purpose: To investigate osseointegration of oral implants, which were retrieved from a patient after 29 years in situ, we use novel three-dimensional analysis methods and visualization techniques that supplement conventional two-dimensional analysis. Materials and Methods: The sample processing involved nondecalcification and embedment in resin. Conventional two-dimensional histomorphometrical methods were conducted. Additionally, the quantification was extended to three-dimensional by using synchrotron radiation micro-computed tomography (SRmCT) technique and two relevant visualization methods for the three-dimensional data were introduced. Results: The three-dimensional results involved three-dimensional quantification and visualization of two implant samples with methods beyond state-of-the-art. Traditional two-dimensional histomorphometrical results revealed a mean bone-implant contact (BIC) of about 50%. In most samples, bone area (BA) was lower inside the treads compared with out-folded mirror images, which were confirmed by the three-dimensional quantification. The BIC along four selected regions showed highest percentages in the bottom/valley region and lowest in the thread-peak region. Qualitative observations revealed ongoing bone remodeling areas in all samples. The apical hole demonstrated high osseointegration. Conclusion: The novel techniques including an animation and an out-folding of BIC and BA enabled a simultaneous visualization of the three-dimensional material obtained from SRmCT data. However, the two-dimensional histological sections were needed for qualitative and quantitative evaluation of osseointegration and, thus, both methods are considered equally important.

  • 32.
    Sarve, Hamid
    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.
    Johansson, Carina B.
    Lindblad, Joakim
    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.
    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.
    Franke-Stenport, Victoria
    Quantification of bone remodeling in the proximity of implants2007In: 12th Int. Conf. on Computer Analysis of Images and Patterns, 2007, p. 253-260Conference paper (Refereed)
    Abstract [en]

    In histomorphometrical investigations of bone tissue modeling around screw-shaped implants, the manual measurements of bone area and bone-implant contact length around the implant are time consuming and subjective. In this paper we propose an automatic image analysis method for such measurements. We evaluate different discriminant analysis methods and compare the automatic method with the manual one. The results show that the principal difference between the two methods occurs in length estimation, whereas the area measurement does not differ significantly. A major factor behind the dissimilarities in the results is believed to be misclassification of staining artifacts by the automatic method.

  • 33.
    Sarve, Hamid
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Centrum för bildanalys, SLU, Uppsala.
    Lindblad, Joakim
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Centrum för bildanalys, SLU, Uppsala.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Centrum för bildanalys, SLU, Uppsala.
    B Johansson, Carina
    Örebro University.
    Att hitta ett histologiskt 2D snitt av ett benimplantat i en 3D mikrotomografivolym2008In: Medicinteknikdagarna 2008, MTF , 2008, p. 103-103Conference paper (Other academic)
  • 34.
    Sarve, Hamid
    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.
    Lindblad, Joakim
    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.
    Borgefors, Gunilla
    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.
    Johansson, Carina B.
    Extracting 3D information on bone remodeling in the proximity of titanium implants in SRμCT image volumes2011In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 102, no 1, p. 25-34Article in journal (Refereed)
  • 35.
    Sarve, Hamid
    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.
    Lindblad, Joakim
    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.
    Johansson, Carina B
    Department of Clinical Medicine, Örebro University.
    Franke-Stenport, Victoria
    Department of Biomaterials, Göteborg University.
    R, Bernhard
    Max-Bergmann-Center of Biomaterials, Institute of Materials Science, Dresden University of Technology.
    D, Scharnweber
    Max-Bergmann-Center of Biomaterials, Institute of Materials Science, Dresden University of Technology.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Sul, Y T
    Image Analysis of Bone Tissue Remodelling Around Implants2007In: European Conference on Biomaterials 2007, 2007Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    Most of the state of the art image analysis programs available on the market have several things in common and irrespective of program, quite a lot of time is needed before results can be obtained.

    There is a need to search for quicker- and reliable histomorphometrical methods in order to screen the implant integration in bone tissue when working on 2D-cut and ground sections. There is a need to find reliable 3D methods in order to provide a better insight in bone modelling and remodelling around implants. We foresee that extracting information obtained with different techniques would help us to gain the understanding of integration of biomaterials.

    This material is a summary of an ongoing project in this topic in the following manner:

    (i) presenting an automatic method for performing quantitative measurements on the histological images and its evaluation.

    (ii)SRµCT imaging of samples and observations made so far.

  • 36.
    Selig, Bettina
    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.
    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.
    Bardage, Stig
    Daniel, Geoffrey
    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.
    Automatic measurement of compression wood cell attributes in fluorescence microscopy images2012In: Journal of Microscopy, ISSN 0022-2720, E-ISSN 1365-2818, Vol. 246, no 3, p. 298-308Article in journal (Refereed)
  • 37.
    Sintorn, Ida-Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Shape based identification of proteins in volume images2005In: Image Analysis: 14th Scandinavian Conference on Image Analysis, SCIA 2005, 2005, p. 253-262Conference paper (Refereed)
    Abstract [en]

    A template based matching method, adapted to the application of identifying individual proteins of a certain kind in volume images, is presented. Grey-level and gradient megnitude information is combined in the watershed algorithm to extract stable borders. These are used in a subsequent hierarchical matching algorithm. The matching algorithm uses a distance transform to serach for local best fits between the edges of a template and edges in the underlying image. It is embedded in a resolution pyramid to decrease the risk of getting stuck in false local minima. This method makes it possible to find proteins attached to other proteins, or proteins appearing as split into parts in the images. It also decreases the amount of human interaction m´needed for identifying individual proteins of the searched kind. The method is demonstrated on a set of three volume images of the antibody IgG in solution.

  • 38.
    Sintorn, Ida-Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Weighted distance transforms for images using elongated voxel grids2002Conference paper (Refereed)
    Abstract [en]

    In this paper we investigate weighted distance transforms in 3D images using elongated voxel grids. We use a local neighbourhood of size 3x3x3 and assume a voxel grid with equal resolution along two axes and lower along the third. The weights (local dista

  • 39.
    Sintorn, Ida-Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    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 for volume images digitized in elongated voxel grids2004In: Pattern Recognition Letters, Vol. 25, p. 571-580Article in journal (Refereed)
    Abstract [en]

    Weighted distance transforms in volume (3D) images using a voxel grid with equal resolution along two axes

    and lower, one, along the third are investigated. The weights (neighbour distances) in a local neighbourhoo

    d of size 3 x 3 x 3 are optimized by minimizing the maximum error in a cubic image.

  • 40.
    Sintorn, Ida-Maria
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Homman-Loudiyi, Mohammed
    Söderberg-Nauclér, Cecilia
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A refined circular template matching method for classification of human cytomegalovirus capsids in TEM images2004In: Computer Methods and Programs in Biomedicine, Vol. 76, p. 95-102Article in journal (Refereed)
    Abstract [en]

    An automatic image analysis method for describing, segmenting, and classifying Human Cyto\-megalo\-virus c

    apsids in transmission electron micrograph (TEM) images of host cell nuclei has been developed. Three stage

    s of the capsid assembly process in the host cell nucleus have been investigated. Each class is described b

    y a radial density profile, which is the average grey-level at each radial distance from the centre. A temp

    late, constructed from the profile, is used to find possible capsid locations by correlation based matching

    . The matching results are further refined by size and distortion analysis of each possible capsid, resulti

    ng in a final segmentation and classification.

  • 41.
    Strand, Robin
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Distance Transforms for Three-Dimensional Grids with Non-Cubic Voxels2005In: Computer Vision and Image Understanding, ISSN 1077-3142, Vol. 100, no 3, p. 294-311Article in journal (Refereed)
    Abstract [en]

    Distance transforms on the face-centered cubic (fcc) grid and the body-centered cubic (bcc) grid are examined. Since the voxels on the fcc and bcc grids are better approximations of a Euclidean ball than the cube, the distance transforms (DTs) on these grids can be less rotation dependent than those in , which is a desirable feature. Optimal (according to the error function) weights are calculated and integer approximations of these weights are found. Also, the two-dimensional city block distance is generalized to the fcc and bcc grids by considering a unit distance between gridpoints whose corresponding voxels share a face. A method to compute the DTs is presented. The results are evaluated both theoretically and by actually computing some DTs.

  • 42.
    Strand, Robin
    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.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Resolution Pyramids on the FCC and BCC Grids2005In: Proceedings of Discrete Geometry for Computer Imagery, 2005, p. 68-78Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    Partitionings on the face-centered cubic grid and the body-centered cubic grid that are suitable for resolution pyramids are found. The partitionings have properties similar to a partitioning that has been used for the resolution pyramids on the cubic grid. Therefore, they are well-suited for adapting methods to construct multiscale representations developed for the cubic grid. Multiscale representations of images are constructed using different methods.

  • 43.
    Strand, Robin
    et al.
    Uppsala University.
    Borgefors, Gunilla
    Uppsala University.
    Weighted Distances on the FCC and BCC Grids2004In: Proceedings SSBA'04 Symposium on Image Analysis, 2004, p. 17-20Conference paper (Other scientific)
    Abstract [en]

    Distance transforms on the fcc grid and the bcc grid are examined. Optimal (according to the error function) weights are calculated and integer approximations for these weights are found. Also, the two-dimensional cityblock distance is generalized to the fcc grid and the bcc grid by considering a unit distance between gridpoints whose corresponding voxels share a face. These distances gives better results than the well-known $D^6$ on the cubic grid.

  • 44.
    Strand, Robin
    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.
    Nagy, Benedek
    Borgefors, Gunilla
    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.
    Digital distance functions on three-dimensional grids2011In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 412, no 15, p. 1350-1363Article in journal (Refereed)
  • 45.
    Strand, Robin
    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.
    Nagy, Benedek
    Fouard, Céline
    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.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Generating Distance Maps with Neighbourhood Sequences2006In: Discrete Geometry for Computer Imagery: 13th International Conference, DGCI 2006, Szeged, Hungary, October 25-27, 2006. Proceedings / [ed] Attila Kuba, László G. Nyúl and Kálmán Palágyi, Berlin, Heidelberg: Springer , 2006, p. 295-307Conference paper (Refereed)
    Abstract [en]

    A sequential algorithm for computing the distance map using distances based on neighbourhood sequences (of any length) in the 2D square grid; and 3D cubic, face-centered cubic, and body-centered cubic grids is presented. Conditions for the algorithm to produce correct results are derived using a path-based approach. Previous sequential algorithms for this task have been based on algorithms that compute the digital Euclidean distance transform. It is shown that the latter approach is not well-suited for distances based on neighbourhood sequences.

  • 46.
    Svensson, Stina
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Digital Distance Transforms in 3D Images Using Information from Neighbourhoods up to 5×5×52002In: Computer Vision and Image Understanding, ISSN 1077-3142, Vol. 88, no 1, p. 24-53Article in journal (Refereed)
    Abstract [en]

    A 3D distance image, or a distance transform, is an image where each feature voxel is labeled with the distance to its closest nonfeature voxel. Distance transforms are useful for many binary (shape) image analysis tasks. The distance transform can be computed by propagating local distance information between neighboring voxels. In a weighted distance transform, the local distances are optimized to make the distance transform more stable under rotation. We present results from optimization for 3D images when using from one to six local distances, all in the 5×5×5 neighborhood of a voxel.

  • 47.
    Svensson, Stina
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Distance transforms in 3D using four different weights2002In: Pattern Recognition Letters, Vol. 23, no 12, p. 1407-1418Article in journal (Refereed)
    Abstract [en]

    Digital distance transformations provide helpful tools for representation and description of object shape in digital images. The resulting distance transforms should be stable under trans ation and rotation. To this end, the Euclidean distance is approxim

  • 48.
    Svensson, Stina
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Borgefors, Gunilla
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Surface Skeletonization of 3D Objects having a Fuzzy Border2002In: Proceedings SSAB'02 Symposium on Image Analysis, 2002, p. 157-160Conference paper (Other scientific)
    Abstract [en]

    Segmentation is a difficult task in image analysis. Here we treat images with objects having a fuzzy border, for which the fuzziness of the border can be estimated. Hence, the images are almost bi-level except for voxels in the border region of the object

  • 49.
    Tizon, Xavier
    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.
    Lin, Qingfen
    Hansen, Tomas
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
    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.
    Johansson, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
    Frimmel, Hans
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
    Identification of the main arterial branches by whole-body contrast-enhanced MRA in elderly subjects using limited user interaction and fast marching2007In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 25, p. 806-814Article in journal (Refereed)
  • 50. Wallin, Hans
    et al.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bildanalys och bildförbättring2005In: Den osynliga matematiken, Liber Ab, Stockholm , 2005, p. 114-115Chapter in book (Other (popular scientific, debate etc.))
12 1 - 50 of 52
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