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28 January 2015 A level set approach for left ventricle detection in CT images using shape segmentation and optical flow
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Proceedings Volume 9287, 10th International Symposium on Medical Information Processing and Analysis; 92870K (2015) https://doi.org/10.1117/12.2073869
Event: Tenth International Symposium on Medical Information Processing and Analysis, 2014, Cartagena de Indias, Colombia
Abstract
The left ventricle (LV) segmentation plays an important role in a subsequent process for the functional analysis of the LV. Typical segmentation of the endocardium wall in the ventricle excludes papillary muscles which leads to an incorrect measure of the ejected volume in the LV. In this paper we present a new variational strategy using a 2D level set framework that includes a local term for enhancing the low contrast structures and a 2D shape model. The shape model in the level set method is propagated to all image sequences corresponding to the cardiac cycles through the optical flow approach using the Hermite transform. To evaluate our strategy we use the Dice index and the Hausdorff distance to compare the segmentation results with the manual segmentation carried out by the physician.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jorge Brieva, Ernesto Moya-Albor, and Boris Escalante-Ramírez "A level set approach for left ventricle detection in CT images using shape segmentation and optical flow", Proc. SPIE 9287, 10th International Symposium on Medical Information Processing and Analysis, 92870K (28 January 2015); https://doi.org/10.1117/12.2073869
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