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  • 51.
    Schold Linnér, Elisabeth
    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.
    Morén, Max
    Smed, Karl-Oskar
    Nysjö, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    LatticeLibrary and BccFccRaycaster: Software for processing and viewing 3D data on optimal sampling lattices2016In: SoftwareX, ISSN 2352-7110, Vol. 5, p. 16-24Article in journal (Refereed)
  • 52.
    Schold Linnér, Elisabeth
    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.
    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.
    Pre-aliasing and anisotropy on the CC, BCC, and FCC sampling latticesManuscript (preprint) (Other academic)
  • 53. Stelldinger, Peer
    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.
    Topology Preserving Digitization with FCC and BCC Grids2006In: Proceedings Combinatorial Image Analysis: 11th International Workshop, IWCIA 2006, 2006, p. 226-240Conference paper (Refereed)
    Abstract [en]

    In digitizing 3D objects one wants as much as possible object properties to be preserved in its digital reconstruction. One of the most fundamental properties is topology. Only recently a sampling theorem for cubic grids could be proved which guarantees topology preservation [1]. The drawback of this theorem is that it requires more complicated reconstruction methods than the direct representation with voxels. In this paper we show that face centered cubic (fcc) and body centered cubic (bcc) grids can be used as an alternative. The fcc and bcc voxel representations can directly be used for a topologically correct reconstruction. Moreover this is possible with coarser grid resolutions than in the case of a cubic grid. The new sampling theorems for fcc and bcc grids also give absolute bounds for the geometric error.

  • 54.
    Strand, Robin
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    A Classification of Centres of Maximal Balls in Z^32005Conference paper (Refereed)
    Abstract [en]

    A classification of centres of maximal balls (CMBs) in Z^3 derived from generalizations of the chessboard and city block metrics to 3D, a weighted metric, and the Euclidean metric is presented. Using these metrics, the set of CMBs (the medial axis) can be extracted. One difficulty with skeletonization in 3D is that of guaranteeing reversibility. A reversible skeleton generally consists of both surfaces and curves. Previous attempts to construct connected skeletons including the CMBs uses conditions based on local neighbourhood configurations. However, a local neighbourhood might be too small and, most important, does not allow a consistent definition for surface- and curve-parts of the skeleton. The classification of the CMBs presented in this paper will be a tool for defining which parts of a 3D skeleton are surfaces and curves.

  • 55.
    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 Sequential Algorithm for Computing the Distance Transform using Distances Based on Neighbourhood Sequences in Z³.2006In: Proceedings SSBA'06 Symposium on Image Analysis, 2006Conference paper (Other academic)
    Abstract [en]

    A sequential algorithm for computing the distance map using distances based on neighbourhood sequences (of any length) in Z³ is presented. Conditions for the algorithm to produce correct results are derived using a path-based approach.

  • 56.
    Strand, Robin
    Uppsala University.
    Detektion av slitna strömavtagare med hjälp av datoriserad bildanalys2003Report (Other scientific)
    Abstract [en]

    In this M.Sc. Thesis work it is examined if, with computerised image analysis, it is possible to automatically decide whether a pantograph is damaged and in need of maintenance. This problem arises in an automatic image analysis system which generates images of trains. In the worst case a damaged pantograph will tear down the contact wire, which is very costly. The thesis work is a part of a project with the purpose to limit the number of torn down contact wires. The report describes a method of doing this and the stability of an implementation of the method. In the segmentation of the contact shoe, a model-based method which matches a template of the part of the pantograph which is of interest is used. The segmentation accuracy is high. The analysis of the contact shoe uses the mean intensity of disjunct regions of the contact shoe. For a reliable analysis of the contact shoe, a more powerful method is needed.

  • 57.
    Strand, Robin
    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.
    Interpolation and Sampling on a Honeycomb Lattice2010In: Proceedings of 20th International Conference on Pattern Recognition, IEEE computer society , 2010, p. 2222-2225Conference paper (Refereed)
    Abstract [en]

    In this paper, we focus on the three-dimensional honeycomb point-lattice in which the Voronoi regions are hexagonal prisms. The ideal interpolation function is derived by using a Fourier transform of the sampling lattice. From these results, the sampling efficiency of the lattice follows.

  • 58.
    Strand, Robin
    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.
    Sampling and Aliasing Properties of Three-Dimensional Point-Lattices2010In: Proceedings SSBA'10 Symposium on Image Analysis, Uppsala, Sweden, 2010 / [ed] Cris Luengo and Milan Gavrilovic, Uppsala: Centre for Image Analysis , 2010, p. 23-26Conference paper (Other academic)
    Abstract [en]

    Sampling properties of some three-dimensional lattices are examined. The Cartesian cubic lattice is compared with the non-Cartesian face- and body-centered cubic lattices. Numerical computations using analytical functions are used to compare rotational dependency and aliasing effects.

  • 59.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Sampling and Ideal Reconstruction on the 3D Diamond Grid2010In: Proceedings of 20th International Conference on Pattern Recognition, Istanbul, Turkey, August 2010, IEEE computer society , 2010, p. 4609-4612Conference paper (Refereed)
    Abstract [en]

    This paper presents basic, yet important, properties that can be used when developing methods for image acquisition, processing, and visualization on the diamond grid. The sampling density needed to reconstruct a band-limited signal and the ideal interpolation function on the diamond grid are derived.

  • 60.
    Strand, Robin
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Shape Representation wtih Maximal Path-Points for Path-Based Distances2007In: Image and Signal Processing and Analysis, 2007. ISPA 2007. 5th International Symposium on, 2007, p. 397-402Conference paper (Refereed)
    Abstract [en]

    A general framework explaining the extraction of maximal path-points (related to the set of centres of maximal balls) for path-based distances is presented. The traditional weigthed distance and distance based on neighbourhood sequences are considered and compared with the recently developed weighted distance based on neighbouhood sequences.

  • 61.
    Strand, Robin
    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.
    Sparse Object Representations by Digital Distance Functions2011In: Proceedings, International Conference on Discrete Geometry for Computer Imagery (DGCI 2011) / [ed] Debled-Rennesson, Isabelle and Domenjoud, Eric and Kerautret, Bertrand and Even, Philippe, Berlin Heidelberg: Springer , 2011, p. 211-222Conference paper (Refereed)
    Abstract [en]

    In this paper, some methods for representing objects usingpath-based distances are considered. The representations can be usedas anchor points when extracting medial representations of the objects.The distance transform (DT) is obtained by labeling each object elementwith the distance to the background. By local operations on the DT,different sets of anchor points can be obtained. We present two differentmethods based on local operations and prove that the representations arereversible, when this is the case. The methods are defined for weighteddistances based on neighborhood sequences, which includes for examplethe well known cityblock and chessboard distances.

  • 62.
    Strand, Robin
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Surface skeletons in grids with non-cubic voxels2004In: Proceedings of International Conference on Pattern Recognition (ICPR 2004), 2004Conference paper (Refereed)
    Abstract [en]

    An algorithm for computing surface skeletons on the face-centered cubic (fcc) grid and the body-centered cubic (bcc) grid is presented. The fcc grid and the bcc grid are three-dimensional grids where the voxels are rhombic dodecahedra and truncated octahedra, respectively. The DT is used to generate the set of centres of maximal balls (CMBs) which will be ``anchor points'' when constructing the skeleton. Simple points are used in order to make the skeleton topologically correct and CMBs to produce a fully reversible skeleton. Using only simple points and the CMBs generates a skeleton with a lot of branches. By using a set of additional conditions for removal and preservation of gridpoints, most of these branches are merged into surfaces. For comparison, the algorithm is also implemented for the cubic grid.

  • 63.
    Strand, Robin
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    The Euclidean Distance Transform Applied to the FCC and BCC Grids2005In: Pattern Recognition and Image Analysis, Proceedings of Second Iberian Conference, IbPRIA 2005: volume 1, 2005, p. 243-250Conference paper (Refereed)
    Abstract [en]

    The discrete Euclidean distance transform is applied to grids with non-cubic voxels, the face-centered cubic (fcc) and body-centered cubic (bcc) grids. These grids are three-dimensional generalizations of the hexagonal grid. Raster scanning and contour processing techniques are applied using different neighbourhoods. When computing the Euclidean distance transform, some voxel configurations produce errors. The maximum errors for the two different grids and neighbourhood sizes are analyzed and compared with the cubic grid.

  • 64.
    Strand, Robin
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    The face-centered cubic grid and the body-centered cubic grid: a literature survey2005Report (Other scientific)
  • 65.
    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.
    Using the Hexagonal Grid for Three-Dimensional Images: Direct Fourier Method Reconstruction and Weighted Distance Transform.2006In: Proceedings of 18th International Conference on Pattern Recognition (ICPR 2006), vol 2, 2006, p. 1169-1172Conference paper (Refereed)
    Abstract [en]

    An image reconstruction technique for computed tomography (CT) images, the direct Fourier method, is shown to apply to non-standard grids. In CT, the 3D image is obtained by reconstructing 2D slices separately. We propose to use the Hexagonal grid for the 2D slices, resulting in 3D images on non-standard grids. Low-level image processing is also considered for these grids – optimal weights to be used for computing the weighted distance transform are calculated.

  • 66.
    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.
    Weighted Distances Based on Neighborhood Sequences for Point-Lattices2009In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 157, no 4, p. 641-652Article in journal (Refereed)
    Abstract [en]

    A path-based distance is defined as the minimal cost-path between two points. One such distance function is the weighted distance based on a neighborhood sequence. It can be defined using any number of neighborhood relations and weights in conjunction with a neighborhood sequence. The neighborhood sequence restricts some steps in the path to a smaller neighborhood. We give formulas for computing the point-to-point distance and conditions for metricity for weighted distances based on neighborhood sequences with two neighborhood relations for the general case of point-lattices.

  • 67.
    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.
    Weighted distances based on neighbourhood sequences2007In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 28, no 15, p. 2029-2036Article in journal (Refereed)
    Abstract [en]

    By combining weighted distances and distances based on neighbourhood sequences, a new family of distance functions with potentially low rotational dependency is obtained. The basic theory for these distance functions, including functional form of the distance between two points, is presented. By minimizing an error function, the weights and neighbourhood sequence that give the distance function with the lowest rotational dependency are derived. To verify that the low rotational dependency of the proposed distance function is valid also in applications, the constrained distance transform on a binary image is computed and compared with some traditionally used distance functions.

  • 68.
    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.
    Weighted Distances Based on Neighbourhood Sequences in Non-Standard Three-Dimensional Grids2007In: Image Analysis, Proceedings / [ed] Ersboll BK, Pedersen KS, 2007, p. 452-461Conference paper (Refereed)
    Abstract [en]

    By combining weighted distances and distances based on neighbourhood sequences, a new family of distance functions with potentially low rotational dependency is obtained. The basic theory for these distance functions, including functional form of the distance between two points, is presented for the face-centered cubic grid and the body-centered cubic grid. By minimizing an error function, the optimal combination of weights and neighbourhood sequence is derived.

  • 69.
    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.

  • 70.
    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.

  • 71.
    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.

  • 72.
    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.
    Brunner, David
    Simple Points on the Body-Centered Cubic Grid2006Report (Other academic)
    Abstract [en]

    Conditions for grid points to be simple on the body-centered cubic (bcc) grid are presented and proved to be correct. For a skeletonization algorithm to be topology-preserving, the concept of simple points is important. We prove that deletion of simple points, according to our definition, on the bcc grid preserves topology. This characterization has been used in a previous paper describing a skeletonization algorithm on the face-centered cubic and the bcc grids. The characterization is also used to prove the correctness of conditions for removing grid points in parallel on the bcc grid.

  • 73.
    Strand, Robin
    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.
    Ciesielski, Krzysztof Chris
    Malmberg, Filip
    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.
    Saha, Punam K.
    The minimum barrier distance2013In: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 117, no 4, p. 429-437Article in journal (Refereed)
    Abstract [en]

    In this paper we introduce a minimum barrier distance, MBD, defined for the (graphs of) real-valued bounded functions f(A), whose domain D is a compact subsets of the Euclidean space R-n. The formulation of MBD is presented in the continuous setting, where D is a simply connected region in R-n, as well as in the case where D is a digital scene. The MBD is defined as the minimal value of the barrier strength of a path between the points, which constitutes the length of the smallest interval containing all values of f(A) along the path. We present several important properties of MBD, including the theorems: on the equivalence between the MBD rho(A) and its alternative definition phi(A); and on the convergence of their digital versions, (rho(A)) over cap and (phi(A)) over cap, to the continuous MBD rho(A) = phi(A) as we increase a precision of sampling. This last result provides an estimation of the discrepancy between the value of (rho(A)) over cap and of its approximation (phi(A)) over cap. An efficient computational solution for the approximation (phi(A)) over cap of (rho(A)) over cap is presented. We experimentally investigate the robustness of MBD to noise and blur, as well as its stability with respect to the change of a position of points within the same object (or its background). These experiments are used to compare MBD with other distance functions: fuzzy distance, geodesic distance, and max-arc distance. A favorable outcome for MBD of this comparison suggests that the proposed minimum barrier distance is potentially useful in different imaging tasks, such as image segmentation. 

  • 74.
    Strand, Robin
    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.
    Ciesielski, Krzysztof Chris
    Department of Mathematics, West Virginia University, Morgantown, USA and Department of Radiology, MIPG, University of Pennsylvania, Philadelphia, USA.
    Malmberg, Filip
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction.
    Saha, Punam K.
    Department of Electrical and Computer Engineering and Department of Radiology, University of Iowa, Iowa City, USA.
    The Minimum Barrier Distance: A Summary of Recent Advances2017In: Lecture Notes in Computer Science book series (LNCS, volume 10502), Switzerland, 2017, Vol. 10502, p. 57-68Conference paper (Refereed)
    Abstract [en]

    In this paper we present an overview and summary of recent results of the minimum barrier distance (MBD), a distance operator that is a promising tool in several image processing applications. The theory constitutes of the continuous MBD in Rn, its discrete formulation in Zn (in two different natural formulations), and of the discussion of convergence of discrete MBDs to their continuous counterpart. We describe two algorithms that compute MBD, one very fast but returning only approximate MBD, the other a bit slower, but returning the exact MBD. Finally, some image processing applications of MBD are presented and the directions of potential future research in this area are indicated.

  • 75.
    Strand, Robin
    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. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology.
    Malmberg, Filip
    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, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Antaros Med AB, BioVenture Hub, Molndal, Sweden.
    Lind, Lars
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cardiovascular epidemiology.
    Sundbom, Magnus
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Upper Abdominal Surgery.
    Ahlström, Håkan
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Antaros Med AB, BioVenture Hub, Molndal, Sweden.
    Kullberg, Joel
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences, Radiology. Antaros Med AB, BioVenture Hub, Molndal, Sweden.
    A concept for holistic whole body MRI data analysis, Imiomics2017In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 2, article id e0169966Article in journal (Refereed)
    Abstract [en]

    Purpose: To present and evaluate a whole-body image analysis concept, Imiomics (imaging omics) and an image registration method that enables Imiomics analyses by deforming all image data to a common coordinate system, so that the information in each voxel can be compared between persons or within a person over time and integrated with non-imaging data.

    Methods: The presented image registration method utilizes relative elasticity constraints of different tissue obtained from whole-body water-fat MRI. The registration method is evaluated by inverse consistency and Dice coefficients and the Imiomics concept is evaluated by example analyses of importance for metabolic research using non-imaging parameters where we know what to expect. The example analyses include whole body imaging atlas creation, anomaly detection, and cross-sectional and longitudinal analysis.

    Results: The image registration method evaluation on 128 subjects shows low inverse consistency errors and high Dice coefficients. Also, the statistical atlas with fat content intensity values shows low standard deviation values, indicating successful deformations to the common coordinate system. The example analyses show expected associations and correlations which agree with explicit measurements, and thereby illustrate the usefulness of the proposed Imiomics concept.

    Conclusions: The registration method is well-suited for Imiomics analyses, which enable analyses of relationships to non-imaging data, e.g. clinical data, in new types of holistic targeted and untargeted big-data analysis.

  • 76.
    Strand, Robin
    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.
    Malmberg, Filip
    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.
    Saha, Punam
    University of Iowa.
    Linnér, Elisabeth
    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.
    The Minimum Barrier Distance - Stability to seed point position2014In: Discrete Geometry for Computer Imagery, DGCI 2014 / [ed] Elena Barcucci, Andrea Frosini, Simone Rinaldi, 2014, p. 111-121Conference paper (Refereed)
    Abstract [en]

    Distance and path-cost functions have been used for image segmentation at various forms, e.g., region growing or live-wire boundary tracing using interactive user input. Different approaches are associated with different fundamental advantages as well as difficulties. In this paper, we investigate the stability of segmentation with respect to perturbations in seed point position for a recently introduced pseudo-distance method referred to as the minimum barrier distance. Conditions are sought for which segmentation results are invariant with respect to the position of seed points and a proof of their correctness is presented. A notion of δ-interface is introduced defining the object-background interface at various gradations and its relation to stability of segmentation is examined. Finally, experimental results are presented examining different aspects of stability of segmentation results to seed point position.

  • 77.
    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.
    Malmberg, Filip
    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.
    Minimal Cost-Path for Path-Based Distances2007In: Proceedings of 5th International Symposium on Image and Signal Processing and Analysis (ISPA 2007), 2007, p. 379-384Conference paper (Refereed)
    Abstract [en]

    Distance functions defined by the minimal cost-path using weights and neighbourhood sequences (n.s.) are considered for the constrained distance transform (CDT). The CDT is then used to find one minimal cost-path between two points. The behaviour of some path-based distance functions is analyzed and a new error function is introduced. It is concluded that the weighted n.s.-distance with two weights (3 x 3 neighbourhood) and the weighted distance with three weights (5 x 5 neighbourhood) have similar properties in terms of minimal cost-path computation, while the former is more efficient to compute.

  • 78.
    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
    A Connection Between Zn and Generalized Triangular Grids2008In: International Symposium on Visual Computing (ISVC 2008), Las Vegas, Nevada, Berlin / Heidelberg: Springer , 2008, p. 1157-1166Conference paper (Refereed)
    Abstract [en]

    In this paper we show how non-standard three-dimensional grids, such as the face-centered cubic (fcc), the body-centered cubic (bcc), and the diamond grids can be embedded in ℤ4. The fcc grid is a hyperplane in ℤ4, the diamond grid is the union of two parallel hyperplanes. The union of four hyperplanes (in a circular way) gives the bcc grid. Based on these connections, several types of neighborhood structures are introduced on these grids. These structures span from the most natural ones (crystal bonds, Voronoi neighbors) to infinite families.

  • 79.
    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
    Faculty of Informatics, University of Debrecen, Debrecen, Hungary.
    A weighted neighbourhood sequence distance function with three local steps2011In: Proceedings of Image and Signal Processing and Analysis (ISPA), 2011 7th International Symposium on, IEEE Computer Society , 2011, p. 564-568Conference paper (Refereed)
    Abstract [en]

    We present a combined weighted neighborhood sequence distance function on the square grid with three types of steps. For this general distance function, we compute parameters that optimize an error function for the asymptotic shape of digital disks. We also analyze approximations of the parameters that can be used in the digital grid used here. An algorithm that can be used for image processing applications is also presented.

  • 80.
    Strand, Robin
    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.
    Nagy, Benedek
    Digital Distance Functions on a Honeycomb Point Lattice2010In: Workshop on Applications of Discrete Geometry and Mathematical Morphology, 2010, p. 17-21Conference paper (Refereed)
    Abstract [en]

    A family of path-based distance functions, weighted distances based on neigh-borhood sequences, are defined on the point lattice in which each Voronoi region (voxel) is a hexagonal prism of arbitrary height. Parameter optimization is performed for differentvalues of the parameter that sets the height of the prisms.

  • 81.
    Strand, Robin
    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.
    Nagy, Benedek
    Distances based on neighbourhood sequences in non-standard three-dimensional grids2007In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 155, no 4, p. 548-557Article in journal (Refereed)
    Abstract [en]

    Properties for distances based on neighbourhood sequences on the face-centred cubic (fcc) and the body-centred cubic (bcc) grids are presented. Formulas to both compute the distances and assure that the distances satisfy the conditions for being metrics are presented and proved to be correct. The formulas are used to calculate the neighbourhood sequences that generates distances with lowest deviation from the Euclidean distance.

  • 82.
    Strand, Robin
    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.
    Nagy, Benedek
    Faculty of Informatics, University of Debrecen, Debrecen, Hungary.
    Path-Based Distance Functions in n-Dimensional Generalizations of the Face- and Body-Centered Cubic Grids2009In: Discrete Applied Mathematics, ISSN 0166-218X, E-ISSN 1872-6771, Vol. 157, no 16, p. 3386-3400Article in journal (Refereed)
    Abstract [en]

    Path-based distance functions are defined on n-dimensional generalizations of the face-centered cubic and body-centered cubic grids. The distance functions use both weights and neighborhood sequences. These distances share many properties with traditional path-based distance functions, such as the city-block distance, but are less rotational dependent. For the three-dimensional case, we introduce four different error functions which are used to find the optimal weights and neighborhood sequences that can be used to define the distance functions with low rotational dependency.

  • 83.
    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
    Some Properties for Distances Based on Neighbourhood Sequences in the Face-Centered Cubic Grid and the Body-Centered Cubic Grid2006Report (Other academic)
  • 84.
    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
    Weighted Neighborhood Sequences in Non-Standard Three-Dimensional Grids -- Parameter Optimization2008In: In Proceedings, theoretical track, International Workshop on Combinatorial Image Analysis (IWCIA 2008), Buffalo, NY, USA, 2008, 2008, p. 51-62Conference paper (Refereed)
    Abstract [en]

    Recently, a distance function was defined on the face-centered cubic and body-centered cubic grids by combining weights and neighborhood sequences. These distances share many properties with traditional path-based distance functions, such as the city-block distance, but are less rotational dependent. We introduce four different error functions which are used to find the optimal weights and neighborhood sequences that can be used to define the distance functions with low rotational dependency.

  • 85.
    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
    Weighted Neighbourhood Sequences in Non-Standard Three-Dimensional Grids: Metricity and Algorithms2008In: In Proceedings International Conference on Discrete Geometry for Computer Imagery (DGCI 2008), Lyon, France, 2008, 2008, p. 201-212Conference paper (Refereed)
    Abstract [en]

    Recently, a distance function was defined on the face- centered cubic and body-centered cubic grids by combining weights and neighbourhood sequences. These distances share many properties with traditional path-based distance functions, such as the city-block distance, but are less rotational dependent. We present conditions for metricity and algorithms to compute the distances.

  • 86.
    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)
  • 87.
    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.

  • 88.
    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.
    Norell, Kristin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    The Polar Distance Transform by Fast-Marching2008In: Proceedings of 19th International Conference on Pattern Recognition (ICPR 2008), Tampa, Florida, December 2008, IEEE computer society , 2008Conference paper (Refereed)
    Abstract [en]

    Image analysis tools that process the image using polar coordinates are needed to avoid the interpolation from polar to cartesian coordinates. We present a tool for analysing and processing circular objects – the polar distance transform computed by fast-marching. The fast marching method can be used for computing the grey-weighted distance transform by numerically approximating the Eikonal differential equation. We modify the Eikonal equation using weights that depend on the radius and angle relative to a pre-defined coordinate system.

  • 89.
    Strand, Robin
    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.
    Normand, Nicolas
    Distance transform computation for digital distance functions2012In: Theoretical Computer Science, ISSN 0304-3975, E-ISSN 1879-2294, Vol. 448, p. 80-93Article in journal (Refereed)
    Abstract [en]

    In image processing, the distance transform (DT), in which each object grid point is assigned the distance to the closest background grid point, is a powerful and often used tool. In this paper, distance functions defined as minimal cost-paths are used and a number of algorithms that can be used to compute the DT are presented. We give proofs of the correctness of the algorithms.

  • 90.
    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.
    Stelldinger, Peer
    Topology Preserving Marching Cubes-like Algorithms on the Face-Centered Cubic Grid2007In: 14th International Conference on Image Analysis and Processing (ICIAP 2007), 2007, p. 781-788Conference paper (Other (popular scientific, debate etc.))
    Abstract [en]

    The well-known marching cubes algorithm is modified to apply to the face-centered cubic (fcc) grid. Thus, the local configurations that are considered when extracting the local surface patches are not cubic anymore. This paper presents three different partitionings of the fcc grid to be used for the local configurations. The three candidates are evaluated theoretically and experimentally and compared with the original marching cubes algorithm. It is proved that the reconstructed surface is topologically equivalent to the surface of the original object when the surface of the original object that is digitized is smooth and a sufficiently dense fcc grid is used.

12 51 - 90 of 90
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