Segmentation of Brain MRI with Reduced Weighted Vectors Using HSOM and FCM Techniques

The proposed Method for automatic segmentation and detection of pathological tissues, normal tissues and CSF of human brain in Magnetic resonance image (MRI) is discussed in this paper. This method is implemented in two phases, (1) the MRI brain image is acquired from patient database, In that film artifact and noise are removed. (2) In second phase, hierarchal self organizing Map and fuzzy ‘C’ means algorithms are used to classify the image layer by layer. The lowest lever weight vector is acquired by the abstraction level. We also achieved a high value of pathological tissue pixels by using Hybrid Intelligence Technique. Our method does not require specific expert definition for each structure or manual interactions during segmentation process. The performance of HSOM-FCM performs more accurate and is compared with previous techniques.