A new stopping force to level set method for medical image segmentation

The class of geometric deformable models, so called level sets has brought tremendous impact to medical imagery due to its capability to preserve topology and fast shape recovery. Robust and efficient segmentation algorithm on digital images are challenging research topic of increasing interest in the decade. It is difficult for radiologist to detect and analyze the suspected area where a mass is overlapped with dense tissues in medical Images. These masses are more readily seen as time progress, but the further the tumor has progressed, the lower the possibility of successful treatment. In this paper to detect accurate size of the masses a new fuzzy rule stopping force for the level set is proposed for segmentation of medical images.