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Proceedings Paper

Coupled deformable models with spatially varying features for quantitative assessment of left ventricular function from cardiac MRI
Author(s): Kirsten Meetz; Jens von Berg; Thomas Netsch; Vladimir Pekar; Steven Lobregt; Roel Truyen; Miriam Siers; Wiro J. Niessen; Michael R. Kaus
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Paper Abstract

Cardiac MRI has improved the diagnosis of cardiovascular diseases by enabling the quantitative assessment of functional parameters. This requires an accurate identification of the myocardium of the left ventricle. This paper describes a novel segmentation technique for automated delineation of the myocardium. We propose to use prior knowledge by integrating a statistical shape model and a spatially varying feature model into a deformable mesh adaptation framework. Our shape model consists of a coupled, layered triangular mesh of the epi- and endocardium. It is adapted to the image by iteratively carrying out i) a surface detection and ii) a mesh reconfiguration by energy minimization. For surface detection a feature search is performed to find the point with the best feature combination. To accommodate the different tissue types the triangles of the mesh are labeled, resulting in a spatially varying feature model. The energy function consists of two terms: an external energy term, which attracts the triangles towards the features, and an internal energy term, which preserves the shape of the mesh. We applied our method to 40 cardiac MRI data sets (FFE-EPI) and compared the results to manual segmentations. A mean distance of about 3 mm with a standard deviation of 2 mm to the manual segmentations was achieved.

Paper Details

Date Published: 15 May 2003
PDF: 11 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.481352
Show Author Affiliations
Kirsten Meetz, Philips Research Labs. (Germany)
Jens von Berg, Philips Research Labs. (Germany)
Thomas Netsch, Philips Research Labs. (Germany)
Vladimir Pekar, Philips Research Labs. (Germany)
Steven Lobregt, Philips Medical Systems (Netherlands)
Roel Truyen, Philips Medical Systems (Netherlands)
Miriam Siers, Univ. Medical Ctr. Utrecht (Netherlands)
Wiro J. Niessen, Univ. Medical Ctr. Utrecht (Netherlands)
Michael R. Kaus, Philips Research Labs. (Germany)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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