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Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

F. Milletari, M. Yigitsoy, N. Navab, A. Ahmadi
Left Ventricle Segmentation in Cardiac Ultrasound Using Hough-Forests With Implicit Shape and Appearance Priors
MICCAI Challenge on Endocardial Three-dimensional Ultrasound Segmentation (CETUS), Boston, MA, September 2014 (bib)

We propose a learning based approach to perform automatic segmentation of the left ventricle in 3D cardiac ultrasound images. The segmentation contour is estimated through the use of a variant of Hough forests whose object localization capabilities are coupled with a patchwise, appearance driven, contour estimation strategy. The performance of the proposed method is evaluated on a dataset of 30 images acquired from 15 patients using different equipment and settings.
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