Fuzzy-ASM Based Automated Skull Stripping Method from Infantile Brain MR Images

Abstract

Automated stripping of skulls from infantile brain MR images is the fundamental work to visualize cerebral surface and to measure cerebral volumes. They are important to evaluate cerebral diseases because most cerebral diseases cause morphometric changes in cerebrum. This study proposes a novel image segmentation method based on fuzzy rule-based active surface model. The proposed method was validated by applying it to two neonatal (3W and 4W) and six infantile (5W to 4Y2M) subjects. The mean sensitivity was 98.84 %, and false-positive rate was 1.21 %, and the cerebral surface was visualized well.