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  • 351.
    Westelius, Carl-Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Wiklund, Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Robust Vergence Control Using Scale--Space Phase Information1992Rapport (Övrigt vetenskapligt)
  • 352.
    Westelius, Carl-Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Wiklund, Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Westin, Carl-Fredrik
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Phase-based Disparity Estimation1995Ingår i: Vision as Process: Basic Research on Computer Vision Systems / [ed] J. L. Crowley, H. I. Christensen, Berlin: Springer-Verlag , 1995, s. 157-178Kapitel i bok, del av antologi (Övrigt vetenskapligt)
    Abstract [en]

    The problem of estimating depth information from two or more images of a scene is one which has received considerable attention over the years and a wide variety of methods have been proposed to solve it [Barnard and Fichsler, 1982; Fleck, 1991]. Methods based on correlation and methods using some form of feature matching between the images have found most widespread use. Of these, the latter have attracted increasing attention since the work of Marr [Marr, 1982], in which the features are zero-crossings on varying scales. These methods share an underlying basis of spatial domain operations.

    In recent years, however, increasing interest has been shown in computational models of vision based primarily on a localized frequency domain representation - the Gabor representation [Gabor, 1946; Adelson and Bergen, 1985], first suggested in the context of computer vision by Granlund [Granlund, 1978].

  • 353.
    Westelius, Carl-Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Westin, Carl-Fredrik
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Focus of Attention Mechanisms using Normalized Convolution1996Ingår i: IEEE transactions on robotics and automation, ISSN 1042-296XArtikel i tidskrift (Refereegranskat)
  • 354.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Bhalerao, A.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Kikinis, Ron
    n/a.
    Using Local 3D Structure for Segmentation of Bone from Computer Tomography Images1997Ingår i: Proceedings of IEEE CVPR 1997: San Juan, Puerto Rico, 1997Konferensbidrag (Refereegranskat)
  • 355.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Granlund, Gösta
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Advanced Image Processing: Introduction and Background1995Ingår i: Vision as Process: eds J.L. Crowley, H.I. Christensen / [ed] J. L. Crowley, H. I. Christensen, Berlin: Springer , 1995Kapitel i bok, del av antologi (Refereegranskat)
  • 356.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    A Parameter Mapping for Line Segmentation1990Rapport (Övrigt vetenskapligt)
  • 357.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    ESPRI Basic Research Action 3038, Vision as Process, DR.A.1.2: Definition of feature generating procedures1991Rapport (Övrigt vetenskapligt)
  • 358.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Estimation of Motion Vector Fields using Tensor Field Filtering1994Ingår i: ICIP: Austin, Texas, IEEE , 1994, s. 237-242Konferensbidrag (Refereegranskat)
  • 359.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Extraction of Local Symmetries Using Tensor Field Filtering1992Ingår i: Proceedings of 2nd Singapore International Conference on Image Processing, 1992, s. 371-375Konferensbidrag (Övrigt vetenskapligt)
  • 360.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Line Extraction using Tensors1995Ingår i: Vision as Process: eds J.L. Crowley H.I. Christensen / [ed] J. L. Crowley, H. I. Christensen, Berlin: Springer , 1995Kapitel i bok, del av antologi (Refereegranskat)
  • 361.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Line Segmentation by Clustering in Möbius-Hough Space1991Rapport (Övrigt vetenskapligt)
  • 362.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Processing Incomplete and Uncertain Data using Subspace Methods1994Ingår i: ICPR12: Jerusalem,Israel, 1994, s. 171-173Konferensbidrag (Refereegranskat)
  • 363.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Representation and Averaging1995Ingår i: Signal Processing for Computer Vision / [ed] Gösta H. Grandlund and Hans Knutsson, Dordrecht: Kluwer , 1995, Vol. 2749, s. 297-308Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    This chapter considers what the important properties are for an information representation to behave well in various transformations. There is an extended discussion on the necessity to separate between class membership and certainty of a signal.

  • 364.
    Westin, Carl-Fredrik
    et al.
    Brigham and Women’s Hospital, Harvard Medical School, Boston, US .
    Knutsson, Hans
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Representation and Estimation of Tensor-Pairs2012Ingår i: New Developments in the Visualization and Processing of Tensor Fields: Part V / [ed] David H. Laidlaw, Anna Vilanova, Springer Berlin/Heidelberg, 2012, s. 267-280Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Over the years, several powerful models have been developed to represent specific elementary signal patterns, e.g. locally linear and planar structures. However, in real world problems there is often a need for handling more than one elementary pattern simultaneously. The straightforward approach of adaptive model selection has proven to be difficult and fragile. At the core of this problem is the vicious intractable search space created by having to simultaneously select models and corresponding samples. This calls for higher order models where multiple patterns are represented as one more complex pattern. In this work, we illustrate the advantages of this approach on data that has bi-modal tensor-valued distributions.The method uses first and second order invariants as a representation, and an eigenvector based solution for recovering the elementary tensor components. We show that this method allows estimation of the two tensors that best represent a given tensor distribution. This distribution can for example be samples from a local neighborhood. A bi-modal distribution will produce the two tensors corresponding to the peaks of the distribution. In addition, numbers indicating the amount of samples belonging to each sub distribution are produced. We demonstrate the potential of the approach by processing a number of simple tensor image examples. The results clearly show that new valuable information regarding the local tensor structure is revealed.

  • 365.
    Westin, Carl-Fredrik
    et al.
    Laboratory of Mathematics in Imaging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA .
    Knutsson, Hans
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Tensor field regularization using normalized convolution2003Ingår i: Computer Aided Systems Theory - EUROCAST 2003: 9th International Workshop on Computer Aided Systems Theory Las Palmas de Gran Canaria, Spain, February 24-28, 2003 Revised Selected Papers / [ed] Roberto Moreno-Díaz and Franz Pichler, Springer Berlin/Heidelberg, 2003, Vol. 2809, s. 564-572Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    This paper presents a filtering technique for regularizing tensor fields. We use a nonlinear filtering technique termed normalized convolution [Knutsson and Westin 1993], a general method for filtering missing and uncertain data. In the present work we extend the signal certainty function to depend on locally derived certainty information in addition to the a priory voxel certainty. This results in reduced blurring between regions of different signal characteristics, and increased robustness to outliers. A driving application for this work has been filtering of data from Diffusion Tensor MRI.

  • 366.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    The Möbius Strip Parameterization for Line Extraction1992Ingår i: Proceedings of ECCV--92, Springer-Verlag , 1992, s. 33-38Konferensbidrag (Refereegranskat)
  • 367.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    The Möbius Strip Parameterization for Line Segmentation1991Ingår i: Proceedings of the SSAB Symposium on Image Analysis: Stockholm, 1991Konferensbidrag (Refereegranskat)
  • 368.
    Westin, Carl-Fredrik
    et al.
    Brigham and Women’s Hospital, Harvard Medical School, Boston.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Kikinis, Ron
    Harvard Medical School, Boston.
    Adaptive Image Filtering2000Ingår i: Handbook of Medical Imaging: Processing and Analysis Management (Biomedical Engineering) / [ed] Isaac Bankman, Academic Press , 2000, , s. 901Kapitel i bok, del av antologi (Övrigt vetenskapligt)
  • 369.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska fakulteten. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten.
    Pasternak, Ofer
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Szczepankiewicz, Filip
    Department of Medical Radiation Physics, Lund University, Lund, Sweden.
    Özarslan, Evren
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Physics, Bogazici University, Istanbul, Turkey.
    van Westen, Danielle
    Department of Diagnostic Radiology, Lund University, Lund, Sweden.
    Mattisson, Cecilia
    Clinical Sciences, Psychiatry, Lund University, Lund, Sweden.
    Bogren, Mats
    Clinical Sciences, Psychiatry, Lund University, Lund, Sweden.
    O'Donnell, Lauren J
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Kubicki, Marek
    Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
    Topgaard, Daniel
    Division of Physical Chemistry, Department of Chemistry, Lund University, Lund, Sweden.
    Nilsson, Markus
    Lund University Bioimaging Center, Lund University, Lund, Sweden.
    Q-space trajectory imaging for multidimensional diffusion MRI of the human brain2016Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 135, s. 345-362Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

  • 370.
    Westin, Carl-Fredrik
    et al.
    Harvard Medical School.
    Martin-Fernandez, Marcos
    University ov Valladolid.
    Alberola-Lopez, Carlos
    University ov Valladolid.
    Ruiz-Alzola, Juan
    University of Las Palmas de Gran Canaria.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Tensor Field Regularization Using Normalized Convolution and Markov Random Fields in a Bayesian Framework2006Ingår i: Visualization and Image Processing of Tensor Fields / [ed] Joachim Weickert, Hans Hagen, Springer Berlin/Heidelberg, 2006, s. 381-398Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    This chapter presents two techniques for regularization of tensor fields. We first present a nonlinear filtering technique based on normalized convolution, a general method for filtering missing and uncertain data. We describe how the signal certainty function can be constructed to depend on locally derived certainty information and further combined with a spatially dependent certainty field. This results in reduced mixing between regions of different signal characteristics, and increased robustness to outliers, compared to the standard approach of normalized convolution using only a spatial certainty field. We contrast this deterministic approach with a stochastic technique based on a multivariate Gaussian signal model in a Bayesian framework. This method uses a Markov random field approach with a 3D neighborhood system for modeling spatial interactions between the tensors locally. Experiments both on synthetic and real data are presented. The driving tensor application for this work throughout the chapter is the filtering of diffusion tensor MRI data.

  • 371.
    Westin, Carl-Fredrik
    et al.
    Harvard Medical School.
    Nilsson, M.
    Lund University.
    Pasternak, O.
    Harvard Medical School.
    Knutsson, Hans
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Diffusion tensors from double-PFG of the human brain2013Ingår i: ISMRM 2013, The International Society for Magnetic Resonance in Medicine , 2013Konferensbidrag (Övrigt vetenskapligt)
  • 372.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Harvard Medical School, Laboratory of Mathematics in Imaging (LMI).
    Nilsson, Markus
    Lund University, Sweden.
    Szczepankiewicz, Filip
    Lund University, Sweden.
    Pasternak, Ofer
    Harvard Medical School.
    Ozarslan, Evren
    Harvard Medical School.
    Topgaard, Daniel
    Lund University, Sweden.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    In-vivo diffusion q-space trajectory imaging2014Ingår i: ISMRM 2014, 2014Konferensbidrag (Övrigt vetenskapligt)
  • 373.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Nordberg, Klas
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    On the Equivalence of Normalized Convolution and Normalized Differential Convolution, Vol. 51994Ingår i: IEEE International Conference on Acoustics, Speech, and Signal Processing, 1994, 1994, s. 457-460Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper establishes an algebraic relation between two methods recently reported; normalized convolution and normalized differential convolution. These are general methods for filtering incomplete or uncertain data and are based on the separation of both data and operator into a signal part and a certainty part. General filtering can be performed without preprocessing input data with an interpolation step. The methods allow both data and operators to be scalars, vectors or tensors of higher order. Normalized differential convolution has been used in a wide range of applications. Examples are estimation of gradient estimation in irregularly sampled data, estimation of differential invariants in sparse image flow fields and image edge effect reduction. It was previously shown that normalized convolution produces a description of the neighbourhood which is optimal in a least square sense. The algebraic relation to normalized differential convolution presented in this paper proves that the latter method is also optimal in the same sense as well.

  • 374.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA .
    Szczepankiewicz, Filip
    Lund University, Sweden.
    Pasternak, Ofer
    Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA.
    Özarslan, Evren
    Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA.
    Topgaard, Daniel
    Lund University, Sweden.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Nilsson, Markus
    Lund University, Sweden.
    Measurement Tensors in Diffusion MRI: Generalizing the Concept of Diffusion Encoding2014Ingår i: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014: 17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part III, Springer, 2014, s. 209-216Konferensbidrag (Refereegranskat)
    Abstract [en]

    In traditional diffusion MRI, short pulsed field gradients (PFG) are used for the diffusion encoding. The standard Stejskal-Tanner sequence uses one single pair of such gradients, known as single-PFG (sPFG). In this work we describe how trajectories in q-space can be used for diffusion encoding. We discuss how such encoding enables the extension of the well-known scalar b-value to a tensor-valued entity we call the diffusion measurement tensor. The new measurements contain information about higher order diffusion propagator covariances not present in sPFG. As an example analysis, we use this new information to estimate a Gaussian distribution over diffusion tensors in each voxel, described by its mean (a diffusion tensor) and its covariance (a 4th order tensor). © 2014 Springer International Publishing.

  • 375.
    Westin, Carl-Fredrik
    et al.
    n/a.
    Westelius, Carl-Johan
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Attention Control for Robot Vision1996Ingår i: CVPR: San Francisco, California, IEEE Computer Society Press , 1996, s. 726-733Konferensbidrag (Refereegranskat)
  • 376.
    Westin, Carl-Fredrik
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Westelius, Carl-Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Wiklund, Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    ESPRIT Basic Research Action 7108, Vision as Process, DR.B.2: Integration of Multi-level Control Loops and FOA1994Rapport (Övrigt vetenskapligt)
  • 377.
    Westin, Carl-Fredrik
    et al.
    Surgical Planning Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
    Wigström, Lars
    Linköpings universitet, Institutionen för medicin och vård, Klinisk fysiologi. Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Hälsouniversitetet.
    Loock, Tomas
    Linköpings universitet, Institutionen för medicin och vård, Radiofysik. Linköpings universitet, Institutionen för medicin och vård, Radiologi. Linköpings universitet, Hälsouniversitetet.
    Sjöqvist, Lars
    Linköpings universitet, Institutionen för medicin och vård, Radiofysik. Linköpings universitet, Institutionen för medicin och vård, Radiologi. Linköpings universitet, Hälsouniversitetet.
    Kikinis, Ron
    Surgical Planning Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik. Linköpings universitet, Hälsouniversitetet.
    Three-dimensional adaptive filtering in magnetic resonance angiography2001Ingår i: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 14, nr 1, s. 63-71Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In order to enhance 3D image data from magnetic resonance angiography (MRA), a novel method based on the theory of multidimensional adaptive filtering has been developed. The purpose of the technique is to suppress image noise while enhancing important structures. The method is based on local structure estimation using six 3D orientation selective filters, followed by an adaptive filtering step controlled by the local structure information. The complete filtering procedure requires approximately 3 minutes of computational time on a standard workstation for a 256 × 256 × 64 data set. The method has been evaluated using a mathematical vessel model and in vivo MRA data (both phase contrast and time of flight (TOF)). 3D adaptive filtering results in a better delineation of small blood vessels and efficiently reduces the high-frequency noise. Depending on the data acquisition and the original data type, contrast-to-noise ratio (CNR) improvements of up to 179% (8.9 dB) were observed. 3D adaptive filtering may provide an alternative to prolonging the scan time or using contrast agents in MRA when the CNR is low.

  • 378.
    Westin, C-F.
    et al.
    Harvard Medical School.
    Nilsson, M.
    Lund University.
    Pasternak, Ofer
    Harvard Medical School.
    Topgaard, D.
    Lund University.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Rotationally invariant gradient schemes for diffusion MRI2012Ingår i: Proceedings of the ISMRM (2012), 2012Konferensbidrag (Övrigt vetenskapligt)
  • 379.
    Westin, C.-F.
    et al.
    Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States, Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School, 75 Francis St., Boston, MA 02115, United States.
    Wigström, Lars
    Linköpings universitet, Hälsouniversitetet. Linköpings universitet, Institutionen för medicin och hälsa, Klinisk fysiologi. Östergötlands Läns Landsting, Hjärtcentrum, Fysiologiska kliniken.
    Loock, T.
    Sjoqvist, L.
    Kikinis, R.
    Surgical Planning Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.
    Knutsson, Hans
    Linköpings universitet, Tekniska högskolan. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik.
    A multielement RF coil for MRI guidance of interventional devices2001Ingår i: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 14, nr 1, s. 56-62Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Accurate localization of minimally invasive devices is critical to the success of interventional procedures. Device orientation and tip position are two of the most important pieces of information needed to define device location for magnetic resonance imaging (MRI)-guided interventional procedures. While a single one-element micro coil incorporated into an interventional device has proven to be effective in some applications, it can only supply tip position information. However, multiple positions on the device are necessary to also determine its orientation. For this purpose, a novel single micro coil design with three separate winding elements that provides both the device orientation and tip position is described in this study. Definition of MR scan planes, by using the device orientation and the target tissue location, permits automatic tracking of the insertion of the device. Furthermore, devices that include this coil design are permitted to bend to a limited extent. This makes the micro coil design appropriate for many flexible interventional devices. Reliable near-real-time tracking of three points on an interventional device is demonstrated on a 0.2T MRI system with modest gradient performance. Phantom and in vivo animal experiments are used to demonstrate the utility of this new coil design. © 2001 Wiley-Liss, Inc.

  • 380.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Haglund, Leif
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta H.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Time Sequence Analysis Using Multi-Resolution Spatio-Temporal Filters1989Ingår i: Time-Varying Image Processing and Moving Object Recognition, 2: Florence, Italy / [ed] V. Cappellini, Amsterdam: Elsevier Science Publishers , 1989, s. 258-265Konferensbidrag (Refereegranskat)
    Abstract [en]

    A methodology for spatio-temporal filtering of image sequences is under development at Computer Vision Laboratory, Linköping University. In later years scale analysis has been found to be a necessary tool in image analysis of stationary images. It is our belief that a combination of spatio-temporal filtering and scale analysis is required to get satisfactory results on image sequences. A growing need and the availability of more powerful computers are the most important reasons for this development. The objectives and proposed methods are discussed in relation to known properties of mammal vision.

  • 381.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    A Generalized Convolver1995Ingår i: SCIA9: Uppsala, Sweden, 1995Konferensbidrag (Refereegranskat)
    Abstract [en]

    A scheme for performing generalized convolutions is presented. A flexible convolver, which runs on standard workstations, has been implemented. It is designed for maximum throughput and flexibility. The implementation incorporates spatio-temporal convolutions with configurable vector combinations. It can handle general multi-linear operations, i.e. tensor operations on multidimensional data of any order. The input data and the kernel coefficients can be of arbitrary vector length. The convolver is configurable for IIR filters in the time dimension. Other features of the implemented convolver are scattered kernel data, region of interest and subsampling. The implementation is done as a C-library and a graphical user interface in AVS (Application Visualization System).

  • 382.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    A Generalized Convolver1996Rapport (Övrigt vetenskapligt)
    Abstract [en]

    A scheme for performing generalized convolutions is presented. A flexible convolver, which runs on standard workstations, has been implemented. It is designed for maximum throughput and flexibility. The implementation incorporates spatio-temporal convolutions with configurable vector combinations. It can handle general multilinear operations, i.e. tensor operations on multidimensional data of any order. The input data and the kernel coefficients can be of arbitrary vector length. The convolver is configurable for IIR filters in the time dimension. Other features of the implemented convolver are scattered kernel data, region of interest and subsampling. The implementation is done as a C-library and a graphical user interface in AVS (Application Visualization System).

  • 383.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Wilson, Roland
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    A Hierarchical Stereo Algorithm1991Rapport (Övrigt vetenskapligt)
  • 384.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Datorseende. Linköpings universitet, Tekniska högskolan.
    Nicolas, Vincent
    Université catholique de Louvain, Communications and Remote Sensing Lab., Place du Levant, 2, B-1348 Louvain-La-Neuve, Belgium.
    Alface, Patrice R.
    Université catholique de Louvain, Communications and Remote Sensing Lab., Place du Levant, 2, B-1348 Louvain-La-Neuve, Belgium.
    Andersson, Mats
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    T-flash: Tensor Visualization in Medical Studio2009Ingår i: Tensors in Image Processing and Computer Vision, Springer London, 2009, s. 455-466Konferensbidrag (Refereegranskat)
    Abstract [en]

    Tensor valued data are frequently used in medical imaging. For a 3-dimensional second order tensor such data imply at least six degrees of freedom for each voxel. The operators ability to perceive this information is of outmost importance and in many cases a limiting factor for the interpretation of the data. In this paper we propose a decomposition of such tensor fields using the Tflash tensor glyphs that intuitively conveys important tensor features to a human observer. A matlab implementation for visualization of single tensors are described in detail and a VTK/ITK implementation for visualization of tensor fields have been developed as a Medical Studio component.

  • 385.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Westelius, Carl-Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Hierarchical Phase Based Disparity Estimation1992Rapport (Övrigt vetenskapligt)
  • 386.
    Wiklund, Johan
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Westelius, Carl-Johan
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Hierarchical Phase Based Disparity Estimation1992Ingår i: Proceedings of 2nd Singapore International Conference on Image Processing: 7-11 September 1992, Singapore / [ed] V. Srinivasan, Ong Sim Heng and Ang Yew Hock, Singapore, River Edge, NJ: World Scientific Publishing , 1992Konferensbidrag (Refereegranskat)
  • 387.
    Wilson, Roland
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    A Multiresolution Stereopsis Algorithm Based on the Gabor Representation1989Ingår i: 3rd International Conference on Image Processing and Its Applications: Warwick, Great Britain, 1989, s. 19-22Konferensbidrag (Refereegranskat)
  • 388.
    Wilson, Roland
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Seeing Things -- Disagreements on the necessary properties of a system that `Recognizes'1992Ingår i: Workshop on Vision: Ruzenagaard, Själlands Udde, 1992, s. 177-189Konferensbidrag (Refereegranskat)
  • 389.
    Wilson, Roland
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Seeing Things [1]1993Rapport (Övrigt vetenskapligt)
  • 390.
    Wilson, Roland
    et al.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Seeing Things II1995Rapport (Övrigt vetenskapligt)
  • 391.
    Wilson, Roland
    et al.
    Warwick University.
    Knutsson, Hans
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Uncertainty and Inference in the Visual System1988Ingår i: IEEE Transactions on Systems, Man and Cybernetics, ISSN 0018-9472, E-ISSN 2168-2909, Vol. 18, nr 2, s. 305-312Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Recent physiological research has indicated that the visual system makes use of units responsive to Gabor signals in the analysis of visual stimuli. Such functions effect a tradeoff between pure spatial- and frequency-domain descriptions. The authors explain the use of such representations in vision, considered as a process in inference from the retinal signals to a symbolic description. The appropriate mathematical structure for the inference is that of the subspaces of the signal vector space, a feature which it shares with quantum mechanics. The theory is derived directly from the fundamental constraints on visual inference. It is then shown to be consistent with many of the known properties of the visual system. In particular, a major feature of the inference system-the occurrence of interference effects-has already been observed in visual system operation

  • 392.
    Wilson, Roland
    et al.
    Univ. of Aston, Birmingham, UK.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta H.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Anisotropic Non-Stationary Image Estimation and its Applications: Part II. Predictive Image Coding1983Ingår i: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 31, nr 3, s. 398-406Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A new predictive coder, based on an estimation method which adapts to line and edge features in images, is described. Quantization of the prediction error is performed by a two-level adaptive scheme: an adaptive transform coder, and a threshold coding in both transform and spatial domains. Control information, which determines the behavior of the predictor, is quantized using a simple variable rate technique. The results are improved by pre- and post-filtering using a related noncausal form of the estimator. Acceptable images have been produced in this way at bit rates of less than 0.5 bit/pixel.

  • 393.
    Wilson, Roland
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta H.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    Image Coding Using a Predictor Controlled by Image Content1982Ingår i: Proceedings of 1982 IEEE Conference on Acoustics, speach and signal processing: Paris, 1982Konferensbidrag (Refereegranskat)
  • 394.
    Wilson, Roland
    et al.
    n/a.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Granlund, Gösta H.
    Linköpings universitet, Institutionen för systemteknik, Bildbehandling. Linköpings universitet, Tekniska högskolan.
    The Operational Definition of the Position of Line and Edge1982Ingår i: The 6th International Conference on Pattern Recognition: Munich, Germany, 1982Konferensbidrag (Refereegranskat)
  • 395.
    Wrangsjö, Andreas
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    A Bayesian approach to image restoration2004Ingår i: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, IEEE , 2004, s. 764-767 vol. 1Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on artificial and real (MRI) image data.

  • 396.
    Wrangsjö, Andreas
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Borga, Magnus
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Adaptive bilateral filters for denoising of digital mammography images2005Ingår i: Symposium on Image Analysis SSBA,2005, 2005, s. 81-84Konferensbidrag (Övrigt vetenskapligt)
  • 397.
    Wrangsjö, Andreas
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Histogram Filters for Noise Reduction2003Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    A class of filters based on histograms are presented. The signal probability density function is estimated and filtering is performed in the pdf domain. Such filters can be designed to preserve signal features such as sharp edges while suppressing stochastic variations. One particular histogram filter scheme is evaluated and compared to a median filter and a normal gaussian blurring filter.

  • 398.
    Wrangsjö, Andreas
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Morphones and brains - non-rigid registration for atlas-based segmentation of MRI volumes2005Ingår i: IFMBE Proceedings: NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics / [ed] Ronnie Lundström, Britt Andersson, Helena Grip, Umeå: IFMBE , 2005, s. 197-198Konferensbidrag (Refereegranskat)
    Abstract [en]

    A method for non-rigid registration of one MRI volume to another is described. The method is presented as a way to perform atlas-based segmen-tation by deformation of a known prototype volume to an unknown MRI volume.

  • 399.
    Wrangsjö, Andreas
    et al.
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Pettersson, Johanna
    Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Knutsson, Hans
    Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska högskolan.
    Non-rigid registration using morphons2005Ingår i: Image Analysis: 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 19-22, 2005. Proceedings / [ed] Heikki Kalviainen, Jussi Parkkinen and Arto Kaarna, Springer Berlin/Heidelberg, 2005, Vol. 3540, s. 501-510Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    The Morphon, a non-rigid registration method is presented and applied to a number of registration applications. The algorithm takes a prototype image (or volume) and morphs it into a target image using an iterative, multi-resolution technique. The deformation process is done in three steps: displacement estimation, deformation field accumulation and deformation. The framework could be described in very general terms, but in this paper we focus on a specific implementation of the Morphon framework. The method can be employed in a wide range of registration tasks, which is shown in four very different registration examples, 2D photographs of hands and faces, 3D CT data of the hip region, and 3D MR brain images.

  • 400.
    Özarslan, Evren
    et al.
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten.
    Yolcu, Cem
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten.
    Herberthson, Magnus
    Linköpings universitet, Matematiska institutionen, Matematik och tillämpad matematik. Linköpings universitet, Tekniska fakulteten.
    Knutsson, Hans
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV.
    Westin, Carl-Fredrik
    Linköpings universitet, Institutionen för medicinsk teknik, Avdelningen för medicinsk teknik. Linköpings universitet, Tekniska fakulteten. Laboratory for Mathematics in Imaging, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA.
    Influence of the Size and Curvedness of Neural Projections on the Orientationally Averaged Diffusion MR Signal2018Ingår i: Frontiers in Physics, E-ISSN 2296-424X, Vol. 6, s. 1-10, artikel-id 17Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Neuronal and glial projections can be envisioned to be tubes of infinitesimal diameter as far as diffusion magnetic resonance (MR) measurements via clinical scanners are concerned. Recent experimental studies indicate that the decay of the orientationally-averaged signal in white-matter may be characterized by the power-law, Ē(q) ∝ q−1, where q is the wavenumber determined by the parameters of the pulsed field gradient measurements. One particular study by McKinnon et al. [1] reports a distinctively faster decay in gray-matter. Here, we assess the role of the size and curvature of the neurites and glial arborizations in these experimental findings. To this end, we studied the signal decay for diffusion along general curves at all three temporal regimes of the traditional pulsed field gradient measurements. We show that for curvy projections, employment of longer pulse durations leads to a disappearance of the q−1 decay, while such decay is robust when narrow gradient pulses are used. Thus, in clinical acquisitions, the lack of such a decay for a fibrous specimen can be seen as indicative of fibers that are curved. We note that the above discussion is valid for an intermediate range of q-values as the true asymptotic behavior of the signal decay is Ē(q) ∝ q−4 for narrow pulses (through Debye-Porod law) or steeper for longer pulses. This study is expected to provide insights for interpreting the diffusion-weighted images of the central nervous system and aid in the design of acquisition strategies.

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