An Automatic Segmentation Method for Brain Tumor Detection using Chan-Vese Algorithm

Biomedical imaging has become an emerging and interesting field for the radiologistsdue to enhancement in technology to resolve the problems. Brain tumor is one of the most threatening diseases to diagnose because of variations in its size, type and location. So, segmentation plays an efficient role in medical field to get the important information from image and helps in better visualization. In this paper, chan-vese algorithm is performed for the segmentation of brain tumor image. Then, binary mask is applied to detect the actual location of tumor. Various features like FOS, FDTA, and GLDS are extracted to classify the tumor. Tumor is detected by this technique and it provides useful results.