Medical image segmentation by fuzzy logic techniques

The paper describes useful fuzzy logic techniques for medical image segmentation. Specific methods to be reviewed include fuzzy information granulation, fuzzy inference and fuzzy cluster identification. Fuzzy information granulation is introduced as a powerful scheme to find the thresholds to obtain the whole brain region in MR data. A fuzzy inference technique succeeds in segmenting the brain region into the left cerebral hemisphere, right cerebral hemisphere, cerebellum and brain stem. The fuzzy inference aided segmentation procedure is also useful for human foot CT images. Fuzzy cluster identification is adapted to determine the obtained clusters into blood vessels or other tissues in an MRA image