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Proceedings Paper

Ischemic segment detection using the support vector domain description
Author(s): Michael S. Hansen; Hildur Ólafsdóttir; Karl Sjöstrand; Søren G. Erbou; Mikkel B. Stegmann; Henrik B. W. Larsson; Rasmus Larsen
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Paper Abstract

Myocardial perfusion Magnetic Resonance (MR) imaging has proven to be a powerful method to assess coronary artery diseases. The current work presents a novel approach to the analysis of registered sequences of myocardial perfusion MR images. A previously reported active appearance model (AAM) based segmentation and registration of the myocardium provided pixel-wise signal intensity curves that were analyzed using the Support Vector Domain Description (SVDD). In contrast to normal SVDD, the entire regularization path was calculated and used to calculate a generalized distance, which is used to discriminate between ischemic and healthy tissue. The results corresponded well to the ischemic segments found by assessment of the three common perfusion parameters; maximum upslope, peak and time-to-peak obtained pixel-wise.

Paper Details

Date Published: 3 March 2007
PDF: 8 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65120F (3 March 2007); doi: 10.1117/12.709492
Show Author Affiliations
Michael S. Hansen, Technical Univ. of Denmark (Denmark)
Hildur Ólafsdóttir, Technical Univ. of Denmark (Denmark)
Karl Sjöstrand, Technical Univ. of Denmark (Denmark)
Søren G. Erbou, Technical Univ. of Denmark (Denmark)
Mikkel B. Stegmann, 3Shape A/S (Denmark)
Henrik B. W. Larsson, Glostrup Hospital (Denmark)
Rasmus Larsen, Technical Univ. of Denmark (Denmark)


Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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