Automated sub-cortical brain structure segmentation combining spatial and deep convolutional features
Brain structure segmentation in Magnetic Resonance Images (MRI) is one of the major interests in medical practice due to its various applications, including pre-operative evaluation and surgical planning, radiotherapy treatment planning, longitudinal monitoring for disease progression or remission (Kikinis et al., 1996; Phillips et al., 2015; Pitiot et al., 2004), etc. The sub-cortical structures (i.e. thalamus, caudate, putamen, pallidum, hippocampus, amygdala, and accumbens) have attracted the interest of the research community for a long time, since their morphological changes are frequently assoc iated with psychiatric and neurodegenerative disorders and could be used as biomarkers of some diseases (Debernard et al., 2015; Mak et al., 2014).
Source: Medical Image Analysis - Category: Radiology Authors: Kaisar Kushibar, Sergi Valverde, Sandra Gonz ález-Villá, Jose Bernal, Mariano Cabezas, Arnau Oliver, Xavier Lladó Source Type: research