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. Author manuscript; available in PMC: 2015 Jan 1.
Published in final edited form as: Med Image Anal. 2013 Oct 14;18(1):118–129. doi: 10.1016/j.media.2013.10.001

Fig. 2.

Fig. 2

Schematic of the automatic segmentation algorithm. The input is shown in light gray and the intermediate products and output are shown in dark gray. First, a set of 3D TEE atlases of the mitral leaflets is generated and a deformable medial model is constructed. Atlas and template generation is performed once. Given a 3D target image to segment, the atlases are registered to the target image and the atlas labels are propagated to the target image to obtain a set of candidate segmentations. Joint label fusion generates a probabilistic consensus segmentation, which is used to guide 3D deformable modeling. The output of the algorithm is a 3D geometric model of the mitral leaflets in the target image.