An Approach of Segmenting Brain Tumor using Self Organising Map.

In all vertebrate and most of invertebrate animal’s brain serves as the area of sensation. The growth of abnormal cells in the brain may leads to the tumor. This tumor can be either cancerous or non-cancerous. The earlier stage of detection and the necessary treatment of tumor may prevent from the human death.The process of segmenting the brain tumor is an important task in the area of medical field. The process of collecting or extracting the pixel values from the MRI brain image based on their intensity values is defined as the brain tumor segmentation. There are many ways available in which the segmentation is achieved. This includes contours, region growing method and the water shed method. The drawbacks of previous segmentation process are overcome by the thresholding method. In order to extract the features of the tissues first the non-specific parts are removed that are not constitutes to the region. Then the filtering process is applied to eliminate the noise from the MRI images. For the process of segmentation Self Organising Map is used along with the class labeling method.We developed an algorithm for clustering instead of using an additional network.Input feature vector is constructed with the features obtained from stationary wavelet transform coefficients.The experimental results show us the higherprecision value and dependability of the proposed tumor segmentation algorithm. This method is highly helpful to estimate the location of the tumor.