“…While prior probabilistic models for brain anatomy and specific diseases have been used (Corso et al, 2008), they are not robust to injury induced brain distortions, as model-subject co-registration often fails (Cuadra et al, 2004; Ghosh et al, 2012a). Curve fitting based methods like active contour snakes (Droske et al, 2001; Liang et al, 2006; Zhou and Xie, 2013), level-set propagation (Droske et al, 2001) and their combined and/or modified versions (Bai et al, 2013; Kazemifar et al, 2014; Le Guyader and Vese, 2008; Liang et al, 2006; Mesejo et al, 2014; Somkantha et al, 2011; Wang et al, 2013) have been applied to medical image segmentation. But these methods suffer from manual interventions (Liang et al, 2006; Zhou and Xie, 2013), computational complexity (Kazemifar et al, 2014; Mesejo et al, 2014), dependence on MRI contrast levels (Kazerooni et al, 2011; Liang et al, 2006; Somkantha et al, 2011) and inadequate cues for efficient registration to prior-models (Bai et al, 2013; Le Guyader and Vese, 2008; Wang et al, 2013) and atlases (Kazemifar et al, 2014), specifically in low-contrast noisy MRI data (Zhou and Xie, 2013).…”