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Wrangsjö, Andreas
Publications (9 of 9) Show all publications
Brun, A., Svensson, B., Westin, C.-F., Herberthson, M., Wrangsjö, A. & Knutsson, H. (2007). Filtering Vector-Valued Images using Importance Sampling. In: Proceedings of the {SSBA} Symposium on Image Analysis,2007: . Paper presented at Symposium on Image Analysis {SSBA}, Linköping, Sweden March 14-15 2007.
Open this publication in new window or tab >>Filtering Vector-Valued Images using Importance Sampling
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2007 (English)In: Proceedings of the {SSBA} Symposium on Image Analysis,2007, 2007Conference paper, Published paper (Other academic)
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38749 (URN)45479 (Local ID)45479 (Archive number)45479 (OAI)
Conference
Symposium on Image Analysis {SSBA}, Linköping, Sweden March 14-15 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-08-28
Brun, A., Svensson, B., Westin, C.-F., Herberthson, M., Wrangsjö, A. & Knutsson, H. (2007). Using Importance Sampling for Bayesian Feature Space Filtering. In: Kjær Bjarne Ersbøll and Kim Steenstrup Pedersen (Ed.), Proceedings of the 15th Scandinavian conference on image analysis: . Paper presented at The 15th Scandinavian conference on image analysis, June 10-24, Aalborg, Denmark (pp. 818-827). Berlin, Heidelberg: Springer-Verlag
Open this publication in new window or tab >>Using Importance Sampling for Bayesian Feature Space Filtering
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2007 (English)In: Proceedings of the 15th Scandinavian conference on image analysis / [ed] Kjær Bjarne Ersbøll and Kim Steenstrup Pedersen, Berlin, Heidelberg: Springer-Verlag , 2007, p. 818-827Conference paper, Published paper (Refereed)
Abstract [en]

We present a one-pass framework for filtering vector-valued images and unordered sets of data points in an N-dimensional feature space. It is based on a local Bayesian framework, previously developed for scalar images, where estimates are computed using expectation values and histograms. In this paper we extended this framework to handle N-dimensional data. To avoid the curse of dimensionality, it uses importance sampling instead of histograms to represent probability density functions. In this novel computational framework we are able to efficiently filter both vector-valued images and data, similar to e.g. the well-known bilateral, median and mean shift filters.

Place, publisher, year, edition, pages
Berlin, Heidelberg: Springer-Verlag, 2007
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; Vol. 4522
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38745 (URN)10.1007/978-3-540-73040-8_83 (DOI)000247364000083 ()45475 (Local ID)978-3-540-73039-2 (ISBN)45475 (Archive number)45475 (OAI)
Conference
The 15th Scandinavian conference on image analysis, June 10-24, Aalborg, Denmark
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-10-08Bibliographically approved
Wrangsjö, A., Borga, M. & Knutsson, H. (2005). Adaptive bilateral filters for denoising of digital mammography images. In: Symposium on Image Analysis SSBA,2005: . Paper presented at SSBA 2005 Symposium on Image Analysis, Malmö, Sweden, 10-11 mars 2005 (pp. 81-84).
Open this publication in new window or tab >>Adaptive bilateral filters for denoising of digital mammography images
2005 (English)In: Symposium on Image Analysis SSBA,2005, 2005, p. 81-84Conference paper, Published paper (Other academic)
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-28784 (URN)13968 (Local ID)13968 (Archive number)13968 (OAI)
Conference
SSBA 2005 Symposium on Image Analysis, Malmö, Sweden, 10-11 mars 2005
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2014-10-08
Wrangsjö, A. & Knutsson, H. (2005). Morphones and brains - non-rigid registration for atlas-based segmentation of MRI volumes. In: Ronnie Lundström, Britt Andersson, Helena Grip (Ed.), IFMBE Proceedings: NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics: . Paper presented at NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics, Umeå, Sweden, June 13th - 17th (pp. 197-198). Umeå: IFMBE
Open this publication in new window or tab >>Morphones and brains - non-rigid registration for atlas-based segmentation of MRI volumes
2005 (English)In: IFMBE Proceedings: NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics / [ed] Ronnie Lundström, Britt Andersson, Helena Grip, Umeå: IFMBE , 2005, p. 197-198Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Umeå: IFMBE, 2005
Series
IFMBE Proceedings, ISSN 1680-0737 ; vol. 9
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-28766 (URN)13943 (Local ID)13943 (Archive number)13943 (OAI)
Conference
NBC'05 13th Nordic Baltic Conference Biomedical Engineering and Medical Physics, Umeå, Sweden, June 13th - 17th
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2013-08-28
Wrangsjö, A., Pettersson, J. & Knutsson, H. (2005). Non-rigid registration using morphons. In: Heikki Kalviainen, Jussi Parkkinen and Arto Kaarna (Ed.), Image Analysis: 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 19-22, 2005. Proceedings (pp. 501-510). Springer Berlin/Heidelberg, 3540
Open this publication in new window or tab >>Non-rigid registration using morphons
2005 (English)In: 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, p. 501-510Chapter in book (Refereed)
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.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 3540
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-48191 (URN)10.1007/11499145_51 (DOI)978-3-540-26320-3 (ISBN)978-3-540-31566-7 (ISBN)3-540-26320-9 (ISBN)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2018-02-08Bibliographically approved
Wrangsjö, A., Borga, M. & Knutsson, H. (2004). A Bayesian approach to image restoration. In: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on: . Paper presented at IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, 15-18 April 2004 (pp. 764-767 vol. 1). IEEE
Open this publication in new window or tab >>A Bayesian approach to image restoration
2004 (English)In: Biomedical Imaging: Nano to Macro, 2004. IEEE International Symposium on, IEEE , 2004, p. 764-767 vol. 1Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
IEEE, 2004
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-22264 (URN)10.1109/ISBI.2004.1398650 (DOI)1438 (Local ID)0-7803-8388-5 (ISBN)1438 (Archive number)1438 (OAI)
Conference
IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Arlington, VA, USA, 15-18 April 2004
Available from: 2009-10-07 Created: 2009-10-07 Last updated: 2014-10-08Bibliographically approved
Wrangsjö, A. (2004). A Bayesian framework for image denoising. (Licentiate dissertation). Linköping: Linköpings universitet
Open this publication in new window or tab >>A Bayesian framework for image denoising
2004 (English)Licentiate thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Linköping: Linköpings universitet, 2004
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1109
Series
LiU-TEK-LIC ; 38
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-30252 (URN)15761 (Local ID)91-85295-07-9 (ISBN)15761 (Archive number)15761 (OAI)
Available from: 2009-10-09 Created: 2009-10-09
Wrangsjö, A. & Knutsson, H. (2003). Histogram Filters for Noise Reduction. In: : . Paper presented at SSBA Symposium on Image Analysis, Stockholm, Sweden 6-7 mars 2003.
Open this publication in new window or tab >>Histogram Filters for Noise Reduction
2003 (English)Conference paper, Published paper (Other academic)
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.

National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-61165 (URN)
Conference
SSBA Symposium on Image Analysis, Stockholm, Sweden 6-7 mars 2003
Available from: 2010-11-09 Created: 2010-11-04 Last updated: 2013-08-28Bibliographically approved
Wrangsjö, A., Fritzson, P. & Sheshadri, K. (1999). Transforming Systems of PDEs for Efficient Numerical Solution. In: : . Paper presented at Third International Mathematica Symposium (IMS 1999), Linz, Austria.
Open this publication in new window or tab >>Transforming Systems of PDEs for Efficient Numerical Solution
1999 (English)Conference paper, Published paper (Refereed)
Abstract [en]

A Mathematica package to deal with a system of partial differential equations (PDEs) is presented. This package usesexplicit finite−difference schemes to handle equations in an arbitrary number of variables that are functions of onespatial variable and time. The code has the flexibility to incorporate any difference approximation specified by theuser, and transforms the given system of PDEs into a system of difference equations that can be iteratively solved using the discretized forms of initial and boundary conditions. The iteration is made considerably faster by converting the Mathematica code into an optimized C++ code using the MathCode C++ compiler[1]. Examples are presented in which the generated C++ code runs about a thousand times faster than the Mathematica code.

Keywords
PDE, partial differential equation, finite-difference, difference approximation, discrete initial conditions, discrete boundary conditions, MathCode C++
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-110165 (URN)
Conference
Third International Mathematica Symposium (IMS 1999), Linz, Austria
Available from: 2014-09-03 Created: 2014-09-03 Last updated: 2014-10-06
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