This proposed work is aimed to develop an automatic method for brain tumor segmentation based on glowworm swarm optimization based fuzzy c-means clustering (GSOFCM) and region growing technique. The proposed method consists of three stages: Stage-1 is accelerating the FCM clustering for tissue segmentation process based on GSO. In Stage-2, is an abnormal detection process that helps to check the results of GSOFCM method by fuzzy symmetric measure (FSM). In Stage-3 is segment the tumor region from abnormal slices by region growing technique. The quantitative analysis of brain tumor segmentation process uses the parameters dice coefficient (DC), positive predictive value (PPV), and processing time. The proposed method is very efficient to segment the tumor region from MRI head scans.

Clustering, Fuzzy c-means, Glowwarm Swarm Optimization, Segmentation

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