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Med Image Comput Comput Assist Interv. 2002 Sep;2488:620-633. doi: 10.1007/3-540-45786-0_77. Epub 2002 Oct 10.

Automated Segmentation of the Left and Right Ventricles in 4D Cardiac SPAMM Images.

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University Of Pennsylvania, Philadelphia, PA 19104, USA.
Biomedical Engineering Department, Rutgers University, New Brunswick, NJ 08854 USA.
New York University, NY, NY 10016 USA.


In this paper we describe a completely automated volume-based method for the segmentation of the left and right ventricles in 4D tagged MR (SPAMM) images for quantitative cardiac analysis. We correct the background intensity variation in each volume caused by surface coils using a new scale-based fuzzy connectedness procedure. We apply 3D grayscale opening to the corrected data to create volumes containing only the blood filled regions. We threshold the volumes by minimizing region variance or by an adaptive statistical thresholding method. We isolate the ventricular blood filled regions using a novel approach based on spatial and temporal shape similarity. We use these regions to define the endocardium contours and use them to initialize an active contour that locates the epicardium through the gradient vector flow of an edgemap of a grayscale-closed image. Both quantitative and qualitative results on normal and diseased patients are presented.

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