Ischemic Segment Detection using the Support Vector Domain Description

Michael Sass Hansen; Hildur Ólafsdóttir; Karl Sjöstrand; Henrik B. Larsson; Mikkel Bille Stegmann; Rasmus Larsen; The International Society for Optical Engineering (SPIE)

Ischemic Segment Detection using the Support Vector Domain Description

Michael Sass Hansen, Hildur Ólafsdóttir, Karl Sjöstrand, Henrik B. Larsson, Mikkel Bille Stegmann, Rasmus Larsen, The International Society for Optical Engineering (SPIE) (Editor)

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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 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. 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.

Original language	English
Title of host publication	International Symposium on Medical Imaging
Publication date	2007
Publication status	Published - 2007
Event	SPIE Medical Imaging 2007 - Town & Country Hotel, San Diego, United States Duration: 17 Feb 2007 → 22 Feb 2007

Conference

Conference	SPIE Medical Imaging 2007
Location	Town & Country Hotel
Country/Territory	United States
City	San Diego
Period	17/02/2007 → 22/02/2007

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title = "Ischemic Segment Detection using the Support Vector Domain Description",

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 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. 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.",

author = "Hansen, {Michael Sass} and Hildur {\'O}lafsd{\'o}ttir and Karl Sj{\"o}strand and Larsson, {Henrik B.} and Stegmann, {Mikkel Bille} and Rasmus Larsen and (SPIE), {The International Society for Optical Engineering}",

year = "2007",

language = "English",

booktitle = "International Symposium on Medical Imaging",

note = "SPIE Medical Imaging 2007 ; Conference date: 17-02-2007 Through 22-02-2007",

}

TY - GEN

T1 - Ischemic Segment Detection using the Support Vector Domain Description

AU - Hansen, Michael Sass

AU - Ólafsdóttir, Hildur

AU - Sjöstrand, Karl

AU - Larsson, Henrik B.

AU - Stegmann, Mikkel Bille

AU - Larsen, Rasmus

A2 - (SPIE), The International Society for Optical Engineering

PY - 2007

Y1 - 2007

N2 - 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 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. 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.

AB - 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 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. 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.

M3 - Article in proceedings

BT - International Symposium on Medical Imaging

T2 - SPIE Medical Imaging 2007

Y2 - 17 February 2007 through 22 February 2007

ER -

Ischemic Segment Detection using the Support Vector Domain Description

Abstract

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