An optimal segmentation method for processing medical image to detect the brain tumor

In the field of medical physics, detection of brain tumor from computed tomography (CT) or magnetic resonance (MRI) scans is a difficult task due to complexity of the brain hence it is one of the top priority goals of many recent researches. In this article, we describe a new method that combines four different steps including smoothing, Sobel edge detection, connected component, and finally region growing algorithms for locating and extracting the various lesions in the brain. The computational algorithm of the proposed method was implemented using Insight Toolkit (ITK). The analysis results indicate that the proposed method automatically and efficiently detected the tumor region from the CT or MRI image of the brain. It is very clear for physicians to separate the abnormal from the normal surrounding tissue to get a real identification of related areas; improving quality and accuracy of diagnosis, which would help to increase success possibility by early detection of tumor as well as reducing surgical planning time. This is an important step in correctly calculating the dose in radiation therapy later.