Fuzzy logic approach to 3D magnetic resonance image segmentation

Abstract

This paper proposes an approach of fuzzy logic to 3D MR image segmentation. We show a fuzzy knowledge representation method to represent the knowledge needed to segment the target portions, and apply our method to 3D MR human brain image segmentation. In it we consider position knowledge, boundary surface knowledge and intensity knowledge. They are expressed by fuzzy if-then rules and compiled to a total degree as the measure of segmentation. The degree is evaluated in region growing technique and which segments the whole brain region into the left cerebral hemisphere, the right cerebral hemisphere, the cerebellum and the brain stem. The experimental result on 36 MR voxel data shows that our method extracted the portions precisely.