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Automatized Evaluation of the Left Ventricular Ejection Fraction from Echocardiographic Images Using Graph Cut
|Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3482|
Published in The MIDAS Journal - Challenge on Endocardial Three-dimensional Ultrasound Segmentation.
Submitted by Olivier Bernard on 10-13-2014.
In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) given 3D echocardiographic images. This is a challenging task due to the poor contrast and the low signal-to-noise ratio typical of echocardiographic images. The method is carried out in 3 steps. First, 3D sampling of the LV cavity is made in a spherical-cylindrical coordinate system. Then, a gradient-based energy term is assigned to each voxel, some of which being given an infinite energy to make sure the resulting volume passes through key anatomical points. Then, a graph-cut procedure provides delineation of the endocardial surface. Results obtained on 30 exams from the 2014 CETUS MICCAI challenge dataset reveal that our method takes between 5 and 10 seconds to segment a 3D volume with an overall mean surface distance lower than 2.3 mm and an ejection fraction error of less than 5% compared to a manual tracing by an expert.
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|Categories:||Feature extraction, Segmentation|
|Keywords:||Segmentation, 3D ultrasound imaging, Graph cuts|
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