Group-wise similarity registration of point sets using Student ’s t-mixture model for statistical shape models

Statistical shape models (SSMs) have found widespread use in a variety of medical image analysis applications in recent years such as segmentation (Patenaude et  al., 2011; Castro-Mateos et al., 2015), shape-based prediction of tissue anisotropy (Lekadir et al., 2014), quantitative shape analysis and classification for computer-aided-diagnosis (Styner et al., 2004; Shen et al., 2012; Gooya et al., 2015b), to name a few. Their primary challenge has per sistently been the availability of training sets of sufficient size, necessary to adequately describe anatomical shape variability observed across different demographic and diagnostic populations.

Source: Medical Image Analysis - December 2, 2017 Category: Radiology Authors: Nishant Ravikumar, Ali Gooya, Serkan Çimen, Alejandro F. Frangi, Zeike A. Taylor Source Type: research