An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Self Organizing Map

Image Segmentation is an important and challenging factor in the medical image segmentation. This paper describes segmentation method consist of two phases. The first phase, describe MRI brain image is acquired from patient’s database, In that film artifact and noise are removed after that HSOM is applied for image segmentation. The HSOM is the extension of the conventional self organizing map used to classify the image row by row. In this lowest level of weight vector, a higher value of tumor pixels, computation speed is achieved by the HSOM with vector quantization.