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LV Challenge LKEB Contribution: Fully Automated Myocardial Contour Detection

Hendriksen, Dennis, Van Assen, Hans, Van der Geest, Rob, Wijnhout, Jeroen
LKEB
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Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3115
Published in The MIDAS Journal - MICCAI 2009 Workshop: Cardiac MR Left Ventricle Segmentation Challenge.
Submitted by Jeroen Wijnhout on 2009-07-31 03:07:56.

In this paper a contour detection method is described and evaluated on the evaluation data sets of the Cardiac MR Left Ventricle Segmentation Challenge as part of MICCAI 2009’s 3D Segmentation Challenge for Clinical Applications. The proposed method, using 2D AAM and 3D ASM, performs a fully automated detection of the myocardial contours, not requiring any user interaction. The algorithm’s performance is reported using the metrics provided by the LV Challenge organization. Endocardial contour detection was classified as successful in 86% of the images and epicardial contours in 94%. The average perpendicular distance (APD) of the successful contours was 2.28 mm and 2.29 mm for the endo- and epicardial contours, respectively.