Computer Aided Brain Tumor Detection via Rule Based Eliminated Watershed Segmentation

Brain cancer is one of the most fateful diseases today. Early diagnosis is of great importance in the treatment of this disease. To accomplish a fast and accurate diagnosis, numerous studies have been performed around the world. In this study, a computer aided tumor detection task is proposed for brain MR images. To prevent over-segmentation a set of methods such as bilateral, gauss, order statistics filters, morphological and sharpening operations are applied for denoising, emphasizing fine details and enhancement steps prior to watershed segmentation. Finally, a rule based elimination is proposed to reduce the false positive detections and increase the performance. Experimental results demonstrate that the proposed method is satisfying to detect brain tumors.