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Farnebäck, Gunnar
Alternative names
Publications (10 of 23) Show all publications
Forsberg, D., Farnebäck, G., Knutsson, H. & Westin, C.-F. (2012). Multi-modal Image Registration Using Polynomial Expansion and Mutual Information. In: Benoit M. Dawant, Gary E. Christensen, J.Michael Fitzpatrick and Daniel Rueckert (Ed.), Benoit M. Dawant, Gary E. Christensen, J.Michael Fitzpatrick and Daniel Rueckert (Ed.), Biomedical Image Registration: Proceedings of the 5th International Workshop, WBIR 2012, Nashville, TN, USA, July 7-8, 2012. Paper presented at International Workshop Biomedical Image Registration, Nashville, TN, USA, July 7-8, 2012 (pp. 40-49). Paper presented at International Workshop Biomedical Image Registration, Nashville, TN, USA, July 7-8, 2012. Springer Berlin/Heidelberg
Open this publication in new window or tab >>Multi-modal Image Registration Using Polynomial Expansion and Mutual Information
2012 (English)In: Biomedical Image Registration: Proceedings of the 5th International Workshop, WBIR 2012, Nashville, TN, USA, July 7-8, 2012 / [ed] Benoit M. Dawant, Gary E. Christensen, J.Michael Fitzpatrick and Daniel Rueckert, Springer Berlin/Heidelberg, 2012, p. 40-49Chapter in book (Refereed)
Abstract [en]

This book constitutes the refereed proceedings of the 5th International Workshop on Biomedical Image Registration, WBIR 2012, held in Nashville, Tennessee, USA, in July 2012. The 20 full papers and 11 poster papers included in this volume were carefully reviewed and selected from 44 submitted papers. They full papers are organized in the following topical sections: multiple image sets; brain; non-rigid anatomy; and frameworks and similarity measures.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2012
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 7359
Keywords
Computer science, Medicine, Radiology, Medical, Computer vision, Optical pattern recognition, Image Processing and Computer Vision, Pattern Recognition, Mathematics of Computing, Probability and Statistics in Computer Science, Imaging / Radiology, Biomedicine general
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-79258 (URN)10.1007/978-3-642-31340-0_5 (DOI)978-3-642-31339-4 (ISBN)978-3-642-31340-0 (ISBN)
Conference
International Workshop Biomedical Image Registration, Nashville, TN, USA, July 7-8, 2012
Funder
Swedish Research Council, 2007-4786
Note

The original publication is available at www.springerlink.com: Daniel Forsberg, Gunnar Farnebäck, Hans Knutsson and  Carl-Fredrik Westin, Multi-Modal Image Registration Using Polynomial Expansion and Mutual Information, 2012, Lecture Notes in Computer Science, (7359), 40-49.http://dx.doi.org/10.1007/978-3-642-31340-0_5. Copyright: Springer-verlag http://www.springerlink.com/.

Available from: 2012-07-11 Created: 2012-07-04 Last updated: 2018-02-15Bibliographically approved
Andersson, M., Smedby, Ö., Sandborg, M., Farnebäck, G. & Hans, K. (2010). Adaptiv filtering of 4D-heart CT for image denoising and patient safety. In: : . Paper presented at MEDICINTEKNIKDAGARNA 2010 6-7 oktober 2010, Umeå.
Open this publication in new window or tab >>Adaptiv filtering of 4D-heart CT for image denoising and patient safety
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2010 (English)Conference paper, Published paper (Other academic)
Abstract [en]

The aim of this medical image science project is to increase patient safety in terms of improved image quality and reduced exposure to ionizing radiation in CT. The means to achieve these goals is to develop and evaluate an efficient adaptive filtering (denoising/image enhancement) method that fully explores true 4D image acquisition modes. Four-dimensional (4D) medical image data are captured as a time sequence of image volumes. During 4D image acquisition, a 3D image of the patient is recorded at regular time intervals. The resulting data will consequently have three spatial dimensions and one temporal dimension. Increasing the dimensionality of the data impose a major increase the computational demands. The initial linear filtering which is the cornerstone in all adaptive image enhancement algorithms increase exponentially with the dimensionality. On the other hand the potential gain in Signal to Noise Ratio (SNR) also increase exponentially with the dimensionality. This means that the same gain in noise reduction that can be attained by performing the adaptive filtering in 3D as opposed to 2D can be expected to occur once more by moving from 3D to 4D. The initial tests on on both synthetic and clinical 4D images has resulted in a significant reduction of the noise level and an increased detail compared to 2D and 3D methods. When tuning the parameters for adaptive filtering is extremely important to attain maximal diagnostic value which not necessarily coincide with an an eye pleasing image for a layman. Although this application focus on CT the resulting adaptive filtering methods will be beneficial for a wide range of 3D/4D medical imaging modalities e.g. shorter acquisition time in MRI and improved elimination of noise in 3D or 4D ultrasound datasets.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-62787 (URN)
Conference
MEDICINTEKNIKDAGARNA 2010 6-7 oktober 2010, Umeå
Available from: 2010-12-03 Created: 2010-12-03 Last updated: 2013-09-05
Ebbers, T. & Farneback, G. (2009). Improving Computation of Cardiovascular Relative Pressure Fields From Velocity MRI. JOURNAL OF MAGNETIC RESONANCE IMAGING, 30(1), 54-61
Open this publication in new window or tab >>Improving Computation of Cardiovascular Relative Pressure Fields From Velocity MRI
2009 (English)In: JOURNAL OF MAGNETIC RESONANCE IMAGING, ISSN 1053-1807, Vol. 30, no 1, p. 54-61Article in journal (Refereed) Published
Abstract [en]

Purpose: To evaluate a multigrid-based solver for the pressure Poisson equation (PPE) with Galerkin coarsening, which works directly on the specified domain, for the computation of relative pressure fields from velocity MRI data. Materials and Methods: We compared the proposed structure-defined Poisson solver to other popular Poisson solvers working on unmodified rectangular and modified quasirectangular domains using synthetic and in vitro phantoms in which the mathematical solution of the pressure field is known, as well as on in vivo MRI velocity measurements of aortic blood flow dynamics. Results: All three PPE solvers gave accurate results for convex computational domains. Using a rectangular or quasirectangular domain on a more complicated domain, like a c-shape, revealed a systematic underestimation of the pressure amplitudes, while the proposed PPE solver, working directly on the specified domain, provided accurate estimates of the relative pressure fields. Conclusion: Popular iterative approaches with quasirectangular computational domains can lead to significant systematic underestimation of the pressure amplitude. We suggest using a multigrid-based PPE solver with Galerkin coarsening, which works directly on the structure-defined computational domain. This solver provides accurate estimates of the relative pressure fields for both simple and complex geometries with additional significant improvements with respect to execution speed.

Keywords
blood pressure measurement; hemodynamics; noninvasive; blood flow
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-20220 (URN)10.1002/jmri.21775 (DOI)
Available from: 2009-09-02 Created: 2009-08-31 Last updated: 2013-09-03
Rydell, J., Johansson, A., Leinard, O. D., Knutsson, H., Farnebäck, G., Lundberg, P. & Borga, M. (2008). Three Dimensional Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging using Inverse Gradient. In: Proceedings of the International Society for Magnetic Resonance in Medicine annual meeting (ISMRM'08): . Paper presented at ISMRM 16th Scientific meeting and Exhibition,Toronto, Canada, 3-9 May 2008 (pp. 1519).
Open this publication in new window or tab >>Three Dimensional Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging using Inverse Gradient
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2008 (English)In: Proceedings of the International Society for Magnetic Resonance in Medicine annual meeting (ISMRM'08), 2008, p. 1519-Conference paper, Published paper (Other academic)
Abstract [en]

Three dimensional phase sensitive reconstruction on two point Dixon volumes has been implemented with use of the inverse gradient. The results has beencompared with the inverse gradient method in two dimensions as well as with the well established region growing method proposed by Ma. The inversegradient method in 3D is able to unwrap the phase field in uncertain regions where the region growing method and the inverse gradient method in 2D cometo a stop.

National Category
Medical Laboratory and Measurements Technologies Computer and Information Sciences
Identifiers
urn:nbn:se:liu:diva-21114 (URN)
Conference
ISMRM 16th Scientific meeting and Exhibition,Toronto, Canada, 3-9 May 2008
Available from: 2009-09-29 Created: 2009-09-29 Last updated: 2019-06-14Bibliographically approved
Farnebäck, G., Rydell, J., Ebbers, T., Andersson, M. & Knutsson, H. (2007). Efficient computation of the inverse gradient on irregular domains. In: 2007 IEEE 11TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1-6. Paper presented at 11th IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, October 14-21 2007 (pp. 2710-2717). IEEE
Open this publication in new window or tab >>Efficient computation of the inverse gradient on irregular domains
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2007 (English)In: 2007 IEEE 11TH INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS 1-6, IEEE , 2007, p. 2710-2717Conference paper, Published paper (Other academic)
Abstract [en]

The inverse gradient problem, finding a scalar field f with a gradient near a given vector field g on some bounded and connected domain Omega epsilon R(n), can be solved by means of a Poisson equation with inhomogeneous Neumann boundary conditions. We present an elementary derivation of this partial differential equation and an efficient multigrid-based method to numerically compute the inverse gradient on non-rectangular domains. The utility of the method is demonstrated by a range of important medical applications such as phase unwrapping, pressure computation, inverse deformation fields, and fiber bundle tracking.

Place, publisher, year, edition, pages
IEEE, 2007
Series
IEEE International Conference on Computer Vision, ISSN 1550-5499 ; VOLS 1-6
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-75811 (URN)10.1109/ICCV.2007.4409176 (DOI)000255099302090 ()978-1-4244-1630-1 (ISBN)
Conference
11th IEEE International Conference on Computer Vision, Rio de Janeiro, Brazil, October 14-21 2007
Available from: 2012-03-12 Created: 2012-03-12 Last updated: 2013-09-03
Rydell, J., Knutsson, H., Pettersson, J., Johansson, A., Farnebäck, G., Dahlqvist Leinhard, O., . . . Borga, M. (2007). Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging Using Inverse Gradient. In: Nicholas Ayache, Sébastien Ourselin, Anthony Maeder (Ed.), Nicholas Ayache, Sebastien Ourselin and Anthony Maeder (Ed.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I: . Paper presented at MICCAI 2007, The 10th International Conference on Medical Image Computing and Computer Assisted Interventio, October 29-November 2, Brisbane, Australia (pp. 210-218). Springer Berlin/Heidelberg
Open this publication in new window or tab >>Phase Sensitive Reconstruction for Water/Fat Separation in MR Imaging Using Inverse Gradient
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2007 (English)In: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007. 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I / [ed] Nicholas Ayache, Sebastien Ourselin and Anthony Maeder, Springer Berlin/Heidelberg, 2007, p. 210-218Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel method for phase unwrapping for phase sensitive reconstruction in MR imaging. The unwrapped phase is obtained by integrating the phase gradient by solving a Poisson equation. An efficient solver, which has been made publicly available, is used to solve the equation. The proposed method is demonstrated on a fat quantification MRI task that is a part of a prospective study of fat accumulation. The method is compared to a phase unwrapping method based on region growing. Results indicate that the proposed method provides more robust unwrapping. Unlike region growing methods, the proposed method is also straight-forward to implement in 3D.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2007
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 4791
Keywords
MRI
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-12661 (URN)10.1007/978-3-540-75757-3_26 (DOI)000250916000026 ()978-3-540-75756-6 (ISBN)978-3-540-75757-3 (ISBN)
Conference
MICCAI 2007, The 10th International Conference on Medical Image Computing and Computer Assisted Interventio, October 29-November 2, Brisbane, Australia
Available from: 2007-11-07 Created: 2007-11-07 Last updated: 2019-06-14
Nordberg, K. & Farnebäck, G. (2005). Estimation of orientation tensors for simple signals by means of second-order filters. Signal Processing: Image Communication, 20(6), 582-594
Open this publication in new window or tab >>Estimation of orientation tensors for simple signals by means of second-order filters
2005 (English)In: Signal Processing: Image Communication, ISSN 0923-5965, Vol. 20, no 6, p. 582-594Article in journal (Refereed) Published
Abstract [en]

Tensors have become a popular tool for representation of local orientation and can be used also for estimation of velocity. A number of computational approaches have been presented for tensor estimation which, however, are difficult to analyze or compare since there has been no common framework in which analysis or comparisons can be made. In this article, we propose such a framework based on second-order filters and show how it applies to three different methods for tensor estimation. The framework contains a few conditions on the filters which are sufficient to obtain correctly oriented rank one tensors for the case of simple signals. It also allows the derivation of explicit expressions for the variation of the tensor across oriented structures which, e.g., can be used to formulate conditions for phase invariance. (c) 2005 Elsevier B.V. All rights reserved.

Keywords
orientation estimation, tensors, second-order filters, volterra series
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-46103 (URN)10.1016/j.image.2005.03.006 (DOI)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2009-11-26
Nordberg, K. & Farnebäck, G. (2003). A Framework for Estimation of Orientation and Velocity. In: International Conference on Image Processing (ICIP): Barcelona, Spain.
Open this publication in new window or tab >>A Framework for Estimation of Orientation and Velocity
2003 (English)In: International Conference on Image Processing (ICIP): Barcelona, Spain, 2003Conference paper, Published paper (Refereed)
Abstract [en]

The paper makes a short presentation of three existing methods for estimation of orientation tensors, the so-called structure tensor, quadrature filter based techniques, and techniques based on approximating a local polynomial model. All three methods can be used for estimating an orientation tensor which in the 3D case can be used for motion estimation. The methods are based on rather different approaches in terms of the underlying signal models. However, they produce more or less similar results which indicates that there should be a common framework for estimation of the tensors. Such a framework is proposed, in terms of a second order mapping from signal to tensor with additional conditions on the mapping. It it also shown that the three methods in principle fall into this framework.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-21603 (URN)10.1109/ICIP.2003.1247180 (DOI)0-7803-7750-8 (ISBN)
Available from: 2009-10-05 Created: 2009-10-05 Last updated: 2010-01-21
Farnebäck, G. (2003). Two-Frame Motion Estimation Based on Polynomial Expansion. In: SCIA13: Gothenburg, Sweden (pp. 363-370).
Open this publication in new window or tab >>Two-Frame Motion Estimation Based on Polynomial Expansion
2003 (English)In: SCIA13: Gothenburg, Sweden, 2003, p. 363-370Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a novel two-frame motion estimation algorithm. The first step is to approximate each neighborhood of both frames by quadratic polynomials, which can be done efficiently using the polynomial expansion transform. From observing how an exact polynomial transforms under translation a method to estimate displacement fields from the polynomial expansion coefficients is derived and after a series of refinements leads to a robust algorithm. Evaluation on the Yosemite sequence shows good results.

Series
Lecture Notes in Computer Science ; 2749
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-21727 (URN)
Available from: 2009-10-25 Created: 2009-10-05 Last updated: 2010-02-10
Farnebäck, G. (2003). Two-frame motion estimation based on polynomial expansion. In: Josef Bigun, Tomas Gustavsson (Ed.), Image Analysis: 13th Scandinavian Conference, SCIA 2003 Halmstad, Sweden, June 29 – July 2, 2003 Proceedings (pp. 363-370). Springer Berlin/Heidelberg, 2749
Open this publication in new window or tab >>Two-frame motion estimation based on polynomial expansion
2003 (English)In: Image Analysis: 13th Scandinavian Conference, SCIA 2003 Halmstad, Sweden, June 29 – July 2, 2003 Proceedings / [ed] Josef Bigun, Tomas Gustavsson, Springer Berlin/Heidelberg, 2003, Vol. 2749, p. 363-370Chapter in book (Refereed)
Abstract [en]

This paper presents a novel two-frame motion estimation algorithm. The first step is to approximate each neighborhood of both frames by quadratic polynomials, which can be done efficiently using the polynomial expansion transform. From observing how an exact polynomial transforms under translation a method to estimate displacement fields from the polynomial expansion coefficients is derived and after a series of refinements leads to a robust algorithm. Evaluation on the Yosemite sequence shows good results.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2003
Series
Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349 ; 2749
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-48575 (URN)10.1007/3-540-45103-X_50 (DOI)3-540-40601-8 (ISBN)978-3-540-40601-3 (ISBN)978-3-540-45103-7 (ISBN)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2018-02-08Bibliographically approved
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