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  • 101.
    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.))
  • 102.
    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.))
  • 103.
    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

  • 104.
    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

  • 105.
    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
    Efficient shape representation by minimizing the set of centres of maximal discs/spheres1997In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 18, no 5, p. 465-471Article in journal (Refereed)
    Abstract [en]

    Efficient shape representations are important for many image processing applications. Distance transform based algorithms can be used to compute the set of centres of maximal discs/spheres, that represents a shape. This paper describes a method that reduc

  • 106.
    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
    Di, Baja Gabriella Sanniti
    Computing skeletons in three dimensions1999In: Pattern Recognition, ISSN 0031-3203, E-ISSN 1873-5142, Vol. 32, no 7, p. 1225-1236Article in journal (Refereed)
    Abstract [en]

    Skeletonization will probably become as valuable a tool for shape analysis in 3D, as it is in 2D. We present a topology preserving 3D skeletonization method which computes both surface and curve skeletons whose voxels are labelled with the D-6 distance to

  • 107.
    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
    Sanniti, di Baja
    Surface Skeletonization of Volume Objects1996In: Advances in Structural and Syntactical Pattern Recognition: 6th International Workshop, SSPR '96 Leipzig, Germany, August 20–23, 1996 Proceedings, Springer Verlag , 1996, p. 251-259Conference paper (Refereed)
  • 108.
    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
    Sanniti, di Baja Gabriella
    Connected Components in 3D Neighbourhoods1997In: SCIA'97, Pattern Recognition Society of Finland , 1997, p. 567-570Conference paper (Refereed)
  • 109.
    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.))
  • 110.
    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.

  • 111.
    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
    Sanniti, di Baja Gabriella
    Skeletonizing Volume Objects. Part II: From Surface to Curve Skeleton1998In: Advances in Pattern Recognition Joint IAPR International Workshops SSPR'98 and SPR'98 Sydney, Australia, August 11–13, 1998 Proceedings, Springer Verlag , 1998, p. 220-229Conference paper (Refereed)
    Abstract [en]

    Volume imaging techniques are becoming common and skeletonization has begun to prove valuable for shape analysis also in 3D. In this paper, a method to reduce solid volume objects to their 3D curve skeletons is presented. The method consists of two major steps.

  • 112.
    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.))
  • 113.
    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.
    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. Humanistisk-samhällsvetenskapliga vetenskapsområdet, Faculty of Arts, Centre for Gender Research. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Centre for Image Analysis Annual Report 20042005Report (Other (popular scientific, debate etc.))
  • 114.
    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.

  • 115.
    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.

  • 116.
    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,

  • 117.
    Brandstedt, S
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Busch, Christer
    Hellström, M
    Nordin, Bo
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Häggman, M
    Neo adjuvant GnRH therapy and radical prostatectomy: Effects on tumorous and benign tissue volumes - A morphometric study1997In: Urological research, ISSN 0300-5623, E-ISSN 1434-0879, Vol. 25, no 1, p. 43-47Article in journal (Refereed)
    Abstract [en]

    The effect on tumour and prostate volumes of a 3-month course of neo-adjuvant hormone therapy was studied using computerised planimetry on serially sectioned specimens obtained by radical prostatectomy. Fifty-four specimens from patients not receiving pre

  • 118.
    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)
  • 119.
    Brandtberg, Tomas
    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.
    Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar2007In: ISPRS journal of photogrammetry and remote sensing (Print), ISSN 0924-2716, E-ISSN 1872-8235, Vol. 61, no 5, p. 325-340Article in journal (Refereed)
    Abstract [en]

    In this paper, a methodology for individual tree-based species classification using high sampling density and small footprint lidar data is clarified, corrected and improved. For this purpose, a well-defined directed graph (digraph) is introduced and it plays a fundamental role in the approach. It is argued that there exists one and only one such unique digraph that describes all four pure events and resulting disjoint sets of laser points associated with a single tree in data from a two-return lidar system. However, the digraph is extendable so that it fits an n-return lidar system (n>2) with higher logical resolution. Furthermore, a mathematical notation for different types of groupings of the laser points is defined, and a new terminology for various types of individual tree-based concepts defined by the digraph is proposed. A novel calibration technique for estimating individual tree heights is evaluated. The approach replaces the unreliable maximum single laser point height of each tree with a more reliable prediction based on shape characteristics of a marginal height distribution of the whole first-return point cloud of each tree. The result shows a reduction of the RMSE of the tree heights of about 20% (stddev=1.1 m reduced to stddev=0.92 m). The method improves the species classification accuracy markedly, but it could also be used for reducing the sampling density at the time of data acquisition. Using the calibrated tree heights, a scale-invariant rescaled space for the universal set of points for each tree is defined, in which all individual tree-based geometric measurements are conducted. With the corrected and improved classification methodology the total accuracy raises from 60% to 64% for classifying three leaf-off individual tree deciduous species (N=200 each) in West Virginia, USA: oaks (Quercus spp.), red maple (Acer ruhrum), and yellow poplar (Liriodendron tuliperifera).

  • 120.
    Brandtberg, Tomas
    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 Species Classification in High Spatial Resolution Aerial Images of Forests using Fuzzy Sets2002In: Fuzzy Sets and Systems, Vol. 132, no 3, p. 371-387Article in journal (Refereed)
    Abstract [en]

    This paper presents an application of fuzzy set theory for classification of individual tree crowns into species groups, in high

  • 121. Bricault, Ivan
    et al.
    Zemiti, Nabil
    Jouniaux, Emilie
    Fouard, Celine
    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.
    Taillant, Elise
    Dorandeu, Frederic
    Cinquin, Philippe
    A light puncture robot for CT and MRI interventions2008In: IEEE Engineering in Medicine and Biology Magazine, ISSN 0739-5175, E-ISSN 1937-4186, Vol. 27, no 3, p. 42-50Article in journal (Refereed)
  • 122.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Extending Distance Computation - Propagating Derivatives2010In: Proceedings SSBA 2010 / [ed] Cris Luengo and Milan Gavrilovic, Uppsala: Centre for Image Analysis , 2010, p. 39-42Conference paper (Other academic)
    Abstract [en]

    In this paper we present a technique to extend distance computation  algorithms that compute global distances from a series of local  updates. This includes algorithms such as the fast marching method  (FMM) and the chamfering algorithm for weighted distances. In  addition to the value of a distance function or distance map, we  derive formulas to compute the gradient and higher order partial  derivatives of the distance function within the same framework. The  approach is based on symbolic differentiation of the update scheme,  which makes it general and straight forward to apply to almost any  distance computation scheme. The main result is a novel set of  ``derivative maps'' that are computed along with the ordinary  distance maps. Apart from the theory itself, these maps and this  technique may be used to compute skeletons and parameterizations  such as Riemannian Normal Coordinates and Gauss Normal Coordinates.

  • 123.
    Brun, Anders
    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.
    Knutsson, Hans
    Department of Medical Engineering, Linköpings Universitet.
    Geodesic Glyph Warping2008In: Proceedings of SSBA, Lund, Sweden: SSBA , 2008Conference paper (Other academic)
  • 124.
    Brun, Anders
    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.
    Knutsson, Hans
    Linköpings Universitet.
    Tensor Glyph Warping: Visualizing Metric Tensor Fields using Riemannian Exponential Maps2009In: Visualization and Processing of Tensor Fields: Advances and Perspectives / [ed] David Laidlaw, Joachim Weickert, Berlin Heidelberg: Springer , 2009, XVII, p. 139-160Chapter in book (Other academic)
    Abstract [en]

    The Riemannian exponential map, and its inverse the Riemannian logarithm map, can be used to visualize metric tensor fields. In this chapter we first derive the well-known metric sphere glyph from the geodesic equation, where the tensor field to be visualized is regarded as the metric of a manifold. These glyphs capture the appearance of the tensors relative to the coordinate system of the human observer. We then introduce two new concepts for metric tensor field visualization: geodesic spheres and geodesically warped glyphs. These extensions make it possible not only to visualize tensor anisotropy, but also the curvature and change in tensor-shape in a local neighborhood. The framework is based on the exp p (v i ) and log p (q) maps, which can be computed by solving a second-order ordinary differential equation (ODE) or by manipulating the geodesic distance function. The latter can be found by solving the eikonal equation, a nonlinear partial differential equation (PDE), or it can be derived analytically for some manifolds. To avoid heavy calculations, we also include first- and second-order Taylor approximations to exp and log. In our experiments, these are shown to be sufficiently accurate to produce glyphs that visually characterize anisotropy, curvature, and shape-derivatives in sufficiently smooth tensor fields where most glyphs are relatively similar in size.

  • 125.
    Brun, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Martin-Fernandez, Marcos
    Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática, Universidad de Valladolid, Spain.
    Acar, Burak
    Munoz-Moreno, Emma
    Cammoun, Leila
    Signal Processing Institute (ITS), Ecole Polytechnique Fédérale Lausanne (EPFL), Lausanne, Switzerland.
    Sigfridsson, Andreas
    Division of Medical Informatics, Department of Biomedical Engineering, Linköping University, Linköping, Spain.
    Sosa-Cabrera, Dario
    Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Svensson, jörn
    Dept. of biomedical Engineering, Linköpings Universitet.
    Herberthson, Magnus
    Dept. of mathematics, linköpings universitet.
    Knutsson, Hans
    Dept of biomedical engineering, Linköpings universitet.
    Similar Tensor Arrays: A Framework for Storage of Tensor Array Data2009In: Tensors in Image Processing and Computer Vision, London: Springer , 2009, 1, p. 407-428Chapter in book (Other academic)
    Abstract [en]

    Abstract This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

  • 126. Brunner, David
    et al.
    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.
    A High-Perpormance Parallel Thinning Approach Using a Non-Cubic Grid Structure.2006Report (Other academic)
    Abstract [en]

    In the past years the so-called body-centered cubic grid (bcc) has been examined and proved to be superior over Cartesian lattices for certain applications. Our work deals with parallel thinning on these bcc grids. We introduce conditions which are sufficient for retaining topology and suggest additional conditions to influence the shape of the resulting skeleton. We further developed an algorithm to extract curve skeletons out of 3d objects in parallel which we also present here.

    We show in our results that the developed thinning approach on bcc grids is extremely efficient.

  • 127.
    Buck, TD
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Ehricke, HH
    Strasser, W
    Thurfjell, Lennart
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    3-D segmentation of medical structures by integration of raycasting with anatomic knowledge1995In: Computers & graphics, ISSN 0097-8493, Vol. 19, no 3, p. 441-449Article in journal (Refereed)
    Abstract [en]

    We present a graphically interactive procedure which is used to register a digital anatomic brain atlas with the tomographic patient volume. Patient structures to be segmented are outlined by local elastic deformation of corresponding objects from the ana

  • 128.
    Cammoun, Leila
    et al.
    Signal Processing Institute Ecole Polytechnique Fédérale de, Lausanne, Switzerland.
    Castaño-Moraga, Carlos Alberto
    Department of Signals and Communciations, University of Las Palmas de Gran Canaria, Spain.
    Muñoz-Moreno, Emma
    Univ. de Valladolid, Spain.
    Sosa-Cabrera, Dario
    Canary Islands Institute of Technology, Spain.
    Acar, Burak
    Electrical-Electronics Eng. Dept, Bogazici University, Istanbul, Turkey.
    Brun, Anders
    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.
    Knutsson, Hans
    Dept. of medical engineering, Linköpings universitet.
    Thiran, Jean-Philippe
    Signal Processing Institute Ecole Polytechnique Fédérale de, Lausanne, Switzerland.
    A Review of Tensors and Tensor Signal Processing2009In: Tensors in Image Processing and Computer Vision / [ed] Santiago Aja-Fernandez, Rodrigo de Luis Garcia, Dacheng Tao, Xuelong Li, London: Springer , 2009, 1, p. 1-32Chapter in book (Other academic)
    Abstract [en]

    Tensors have been broadly used in mathematics and physics, since they are a generalization of scalars or vectors and allow to represent more complex properties. In this chapter we present an overview of some tensor applications, especially those focused on the image processing field. From a mathematical point of view, a lot of work has been developed about tensor calculus, which obviously is more complex than scalar or vectorial calculus. Moreover, tensors can represent the metric of a vector space, which is very useful in the field of differential geometry. In physics, tensors have been used to describe several magnitudes, such as the strain or stress of materials. In solid mechanics, tensors are used to define the generalized Hooke’s law, where a fourth order tensor relates the strain and stress tensors. In fluid dynamics, the velocity gradient tensor provides information about the vorticity and the strain of the fluids. Also an electromagnetic tensor is defined, that simplifies the notation of the Maxwell equations. But tensors are not constrained to physics and mathematics. They have been used, for instance, in medical imaging, where we can highlight two applications: the diffusion tensor image, which represents how molecules diffuse inside the tissues and is broadly used for brain imaging; and the tensorial elastography, which computes the strain and vorticity tensor to analyze the tissues properties. Tensors have also been used in computer vision to provide information about the local structure or to define anisotropic image filters.

  • 129.
    Carlbom, Ingrid
    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.
    Kapur, Tina
    Klinker, Gudrun
    Terzopoulos, Demitri
    Thurfjell, Lennart
    General-Purpose Soft Tissue Segmentation from Medical Images1995In: SCIA'9, Swedish Society of Automated Image Analysis , 1995, p. 905-912Conference paper (Refereed)
  • 130.
    Chanussot, Jocelyn
    et al.
    Signal and Image Laboratory (LIS, Grenoble).
    Nyström, Ingela
    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.
    Sladoje, Natasa
    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.
    Shape signaturs of fuzzy star-shaped sets based on distance from the centroid2005In: Pattern Recognition Letters, ISSN 0167-8655, Vol. 26, no 6, p. 735-746Article in journal (Refereed)
    Abstract [en]

    We extend the shape signature based on the distance of the boundary points from the shape centroid, to the case of fuzzy sets. The analysis of the transition from crisp to fuzzy shape descriptor is first given in the continuous case. This is followed by a study of the specific issues induced by the discrete representation of the objects in a computer.

    We analyze two methods for calculating the signature of a fuzzy shape, derived from two ways of defining a fuzzy set: first, by its membership function, and second, as a stack of its α-cuts. The first approach is based on measuring the length of a fuzzy straight line by integration of the fuzzy membership function, while in the second one we use averaging of the shape signatures obtained for the individual α-cuts of the fuzzy set. The two methods, equivalent in the continuous case for the studied class of fuzzy shapes, produce different results when adjusted to the discrete case. A statistical study, aiming at characterizing the performances of each method in the discrete case, is done. Both methods are shown to provide more precise descriptions than their corresponding crisp versions. The second method (based on averaged Euclidean distance over the α-cuts) outperforms the others.

  • 131. Chinga-Carrasco, Gary
    et al.
    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.
    Eriksen, Øyvind
    Svensson, Stina
    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.
    Structural characteristics of pore networks affecting print-through2008In: Journal of Pulp and Paper Science (JPPS), ISSN 0826-6220, Vol. 34, no 1, p. 13-22Article in journal (Refereed)
    Abstract [en]

    The pore structure of handsheets and of commercial newsprints is described in detail. The advantages and limitations of scanning electron microscopy and synchrotron radiation X-ray microtomography for pore-structure assessment are discussed. This gives insight into the two-dimensional and three-dimensional characteristics of the pore structure. A major achievement is the effective quantification of the submicron pores by scanning electron microscopy. It is demonstrated that submicron pores contribute positively to light scattering per unit thickness. The relationship between the pore structure, the light scattering and print-through is explored.

  • 132.
    Choi, Heung-Kook
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    New Methods for Image Analysis of Tissue Sections1996Doctoral thesis, comprehensive summary (Other academic)
  • 133.
    Choi, Heung-Kook
    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.
    Bengtsson, Ewert
    Jarkrans, Torsten
    Vasko, Janus
    Wester, Kenneth
    Malmström, Per-Uno
    Busch, Christer
    Minimum Spanning Trees (MST) as a Tool for Describing Tissue Architecture when Grading Bladder Carcinoma1995In: 8th International Conference on Image Analysis and Processing: ICIAP'95 San Remo, Italy, September 13–15, 1995 Proceedings, Springer Verlag , 1995, p. 615-620Conference paper (Refereed)
  • 134.
    Choi, Heung-Kook
    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.
    Jarkrans, Torsten
    Bengtsson, Ewert
    Vasko, Janus
    Wester, Kenneth
    Malmstrom, Per-Uno
    Busch, Christer
    Image analysis based grading of bladder carcinoma. Comparison of object, texture and graph based methods and their reproducibility1997In: Analytical Cellular Pathology, ISSN 0921-8912, E-ISSN 1878-3651, Vol. 15, no 1, p. 1-18Article in journal (Refereed)
    Abstract [en]

    The possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried

  • 135.
    Choi, Hyun-Ju
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Image analysis for quantifying microvessel density in renal cell carcinoma2009In: Journal of Korea Society of Medical Informatics, ISSN 1225-8903, Vol. 15, no 2, p. 217-225Article in journal (Refereed)
    Abstract [en]

    The most widely used method for quantifying new blood vessel growth in tumor angiogenesis is the determination of microvessel density, which is reported to be associated with tumor progression and metastasis, and a prognostic indicator of patient outcome. In this study, we propose a method for the determination of microvessel density by image analysis, to improve the accuracy and the objectivity of determination of the microvessel density. Four-micron-thick tissue sections of renal cell carcinoma samples were stained immunohistochemically for CD34. The regions with a high degree of vascularization were selected by an expert for digitization. Each image was digitized as a 24-bits/pixel image file with a resolution of 640×480 pixels. First, segmentation of the microvessels based on pixel classification using color features in hybrid color space was performed. After use of a correction process for microvessels with discontinuities and separation of touching microvessels, we counted the number of microvessels for the microvessel density measurement. The result was evaluated by comparison with manual quantification of the same images. The comparison revealed that our computerized microvessel quantification was highly correlated with manual counting by a pathologist. The results indicate that our method is better than the conventional computerized image analysis methods.

  • 136.
    Chunming, Tang
    et al.
    Harbin Engineering University, China.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Automatic Tracking of Neural Stem Cells2005In: WDIC 2005: Workshop Proceedings, 2005, p. 61-66Conference paper (Refereed)
    Abstract [en]

    In order to understand the development of stem-cells into specialized mature cells it is necessary to study the growth of cells in culture. For this purpose it is very useful to have an efficient computerized cell tracking system. In this paper a prototype system for tracking neural stem cells in a sequence of images is described. The system is automatic as far as possible but in order to get as complete and correct tracking results as possible the user can interactively verify and correct the crucial starting segmentation of the first frame and inspect the final result and correct errors if nec-

    essary. All cells are classified into inactive, active, dividing and clustered cells. Different algorithms are used to deal with the different cell categories. A special backtracking step is used to automatically correct for some common errors that appear in the initial forward tracking process.

  • 137.
    Coeurjolly, David
    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.
    Estimation of Curvature along Curves with Application to Fibres in 3D Images of Paper2003Conference paper (Refereed)
    Abstract [en]

    Space curves can be used to represent elongated objects in 3D images and furthermore to facilitate the computation of shape measures for the represented objects. In our specific application (fibres in 3D images of paper), we want to analyze the fibre net

  • 138.
    Cristea, Alexander
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience.
    Karlsson Edlund, Patrick
    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.
    Qaisar, Rizwan
    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.
    Larsson, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Effects of ageing and gender on the spatial organisation of nuclei in single human skeletal muscle cells2009In: Neuromuscular Disorders, ISSN 0960-8966, E-ISSN 1873-2364, Vol. 19, no 8, p. 605-606Article in journal (Refereed)
  • 139.
    Cristea, Alexander
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Karlsson Edlund, Patrick
    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.
    Qaisar, Rizwan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    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.
    Larsson, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Effects of ageing and gender on the spatial organization of nuclei in single human skeletal muscle cells2009In: Neuromuscular Disorders, ISSN 0960-8966, E-ISSN 1873-2364, Vol. 19, p. 605-606Article in journal (Refereed)
  • 140.
    Cristea, Alexander
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Qaisar, Rizwan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Karlsson Edlund, Patrick
    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.
    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.
    Larsson, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Neuroscience, Clinical Neurophysiology.
    Effects of aging and gender on the spatial organization of nuclei in single human skeletal muscle cells2010In: Aging Cell, ISSN 1474-9718, E-ISSN 1474-9726, Vol. 9, no 5, p. 685-697Article in journal (Refereed)
    Abstract [en]

    The skeletal muscle fibre is a syncitium where each myonucleus regulates the gene products in a finite volume of the cytoplasm, i.e., the myonuclear domain (MND). We analysed aging- and gender-related effects on myonuclei organization and the MND size in single muscle fibres from six young (21–31 years) and nine old men (72–96 years), and from six young (24–32 years) and nine old women (65–96 years), using a novel image analysis algorithm applied to confocal images. Muscle fibres were classified according to myosin heavy chain (MyHC) isoform expression. Our image analysis algorithm was effective in determining the spatial organization of myonuclei and the distribution of individual MNDs along the single fibre segments. Significant linear relations were observed between MND size and fibre size, irrespective age, gender and MyHC isoform expression. The spatial organization of individual myonuclei, calculated as the distribution of nearest neighbour distances in 3D, and MND size were affected in old age, but changes were dependent on MyHC isoform expression. In type I muscle fibres, average NN-values were lower and showed an increased variability in old age, reflecting an aggregation of myonuclei in old age. Average MND size did not change in old age, but there was an increased MND size variability. In type IIa fibres, average NN-values and MND sizes were lower in old age, reflecting the smaller size of these muscle fibres in old age. It is suggested that these changes have a significant impact on protein synthesis and degradation during the aging process.

  • 141.
    Curic, Vladimir
    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.
    Sladoje, Natasa
    Centre for Mathematics and Statistics, Faculty of Technical Sciences, University of Novi Sad, Serbia.
    The Sum of minimal distances as a useful distance measure for image registration2010In: Proceedings SSBA 2010 / [ed] Cris Luengo and Milan Gavrilovic, Uppsala: Centre for Image Analysis , 2010, p. 55-58Conference paper (Other academic)
    Abstract [en]

    In this paper we study set distances which are used in image registration related problems. We introduced a new distance as a Sum of minimal distances with added linear weights. Linear weights are added in a way to reduce the impact of single outliers. An evaluation of observed distances with respect to applicability to image object registration is performed. A comparative study of set distances with respect to noise sensitivity as well as with respect to translation and rotation of objects in image is presented. Based on our experiments on synthetic images containing various types of noise, we determine that the proposed weighted sum of minimal distances has a good performances for object registration.

  • 142.
    Dahlqvist, Bengt
    et al.
    Uppsala University.
    Nordin, Bo
    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.
    Recognition and Classification of Cancer Cells in an Image Analysis System1988Report (Other academic)
  • 143. Degerman, Johan
    et al.
    Althoff, Karin
    Thorlin, Thorleif
    Wählby, Carolina
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Karlsson, Patrick
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Bengtsson, Ewert
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Gustavsson, Tomas
    Modeling stem cell migration by Hidden Markov2004In: Proceedings of the Swedish Symposium on Image Analysis, SSBA 2004, 2004, p. 122-125Conference paper (Other scientific)
  • 144.
    Egevad, Lars
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Frimmel, Hans
    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.
    Mattson, Stefan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    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.
    Busch, Christer
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Biopsy protocol stability in a three-dimensional model of prostate cancer: Changes in cancer yield after adjustment of biopsy positions1999In: Urology, ISSN 0090-4295, E-ISSN 1527-9995, Vol. 54, p. 862-868Article in journal (Refereed)
  • 145.
    Egevad, Lars
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Frimmel, Hans
    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.
    Norberg, Mona
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Oncology, Radiology and Clinical Immunology, Radiology.
    Mattson, Stefan
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Information Science, Statistics.
    Carlbom, Ingrid
    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.
    Busch, Christer
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology.
    Three-dimensional computer reconstruction of prostate cancer from radical prostatectomy specimens: Evaluation of the model by core biopsy simulation1999In: Urology, ISSN 0090-4295, E-ISSN 1527-9995, Vol. 53, p. 192-198Article in journal (Refereed)
  • 146.
    Eliasson, Daniel
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    On measuring the intersection length of a line and a digital volume2003Report (Other scientific)
    Abstract [en]

    This Master Thesis investigates methods to calculate the

  • 147. Engbrant, Fredrik
    et al.
    Monazzam, Azita
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences.
    Svensson, Per-Edvin
    Olsson, Johan
    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.
    Razifar, Pasha
    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.
    Signal Extraction and Separation in In Vivo Animal PET Studies with Masked Volumewise Principal-Component Analysis2010In: Journal of Nuclear Medicine Technology, ISSN 0091-4916, E-ISSN 1535-5675, Vol. 38, no 2, p. 53-60Article in journal (Refereed)
    Abstract [en]

    The standardized uptake value is commonly used as a tool tosupplement visual interpretation and to quantify the imagesacquired from static in vivo animal PET. The preferred approachfor analyzing PET data is either to sum the images and calculatethe standardized uptake value or to use kinetic modeling. Theaim of this study was to investigate the performance of maskedvolumewise principal-component analysis (MVW-PCA) used in dynamicin vivo animal PET studies to extract and separate signals withdifferent kinetic behaviors. Methods: PET data were acquiredwith a small-animal PET scanner and a fluorine tracer in a studyof rats and mice. After acquisition, the data were reconstructedby use of 4 time protocols with different frame lengths. Datawere analyzed by use of MVW-PCA with applied noise prenormalizationand a new masking technique developed in this study. Results:The resulting principal-component images showed a clear separationof the activity in the spine into the first MVW-PCA componentand the activity in the kidneys into the second MVW-PCA component.In addition, the different time protocols were shown to havelittle or no impact on the results obtained with MVW-PCA. Conclusion:MVW-PCA can efficiently separate different kinetic behaviorsinto different principal-component images. Moreover, MVW-PCAis a stable technique in the sense that the time protocol chosenhas only a small impact on the resulting principal-componentimages.

  • 148.
    Ericsson, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology.
    Hast, Anders
    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, Department of Information Technology.
    Design and Implementation of a Stereoscopic Display in a Lecture-room2008In: SIGRAD 2008: The Annual SIGRAD Conference Special Theme: Interaction, November 27–28, 2008 Stockholm, Sweden, Linköping University Electronic Press , 2008, p. 79-80Conference paper (Refereed)
    Abstract [en]

    This paper describes the master thesis project 3DIS4U: Design and implementation of a distributed visualization system with a stereoscopic display carried out at Uppsala University. The main contributions of the thesis are the installation and evaluation of a wallsized stereoscopic display in a class room-like environment and improvement of the quality, interactivity and usability of visualizations at Uppsala University by connecting the system to one of UPPMAX high-performance computing (HPC) clusters. The project involved modifications to open source softwares, mainly the Visualization ToolKit (VTK) and ParaView. Furthermore, software was developed to aid users in creating interactive stereoscopic simulations. Software was installed and modified for better usability. The option of using HPC resources for larger interactive visualizations also exists. As a final step, evaluations of the display and of the software were carried out together with background research on distributed rendering techniques to be able to produce a proposal for further development of the project. The result of this work is a class room environment which in a few minutes can be turned into a visualization studio with a stereoscopic Linköpings universitetdisplay with the ability to create interactive visualizations. The lecture room retains its function as a class room and can support up to 30 simultaneous viewers.

  • 149.
    Erikson, M.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Structure-Keeping Colour Segmentation of Tree Crowns in Aerial Images2001Conference paper (Refereed)
    Abstract [en]

    A new method for colour segmentation of tree crowns in aerial images is

  • 150.
    Erikson, Mats
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Colour segmentation of individual tree crowns in aerial images2002In: Proceedings SSAB'02, 2002, p. 177-180Conference paper (Other scientific)
    Abstract [en]

    A method based on region growing for segmentation of tree crowns in aerial photographs is presented. By using a decision function, for including a pixel or not, both in the spatial domain and in the colour domain, the structure of the contour of the tree

1234567 101 - 150 of 683
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