9 March 2010 Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach
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Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information-gradient, intensity distributions, and regional-property terms-are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Honghai Zhang, Honghai Zhang, Ademola K. Abiose, Ademola K. Abiose, Dwayne N. Campbell, Dwayne N. Campbell, Milan Sonka, Milan Sonka, James B. Martins, James B. Martins, Andreas Wahle, Andreas Wahle, } "Left-ventricle segmentation in real-time 3D echocardiography using a hybrid active shape model and optimal graph search approach", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 76261C (9 March 2010); doi: 10.1117/12.844357; https://doi.org/10.1117/12.844357

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