BRAIN TUMOR DETECTION WITH MRI IMAGE USING ANISOTROPHIC FILTER AND SEGMENTATION

Abstract

The early detection of cancer can be helpful in complete curing the disease. According to the most research in developed countries shows results that just because of inaccurate detection the numbers of people who have brain tumor were died. As the use of digital images has rapidly increased over the past decade, Radiologists by using computed Tomography (CT scan) and Magnetic Resonance Imaging (MRI) examine the patient physically. In surgical & medical assessments, brain tumor segmentation using MRI images is very difficult and important task. For diagnosis of brain tumor MR image is visually examined by the physician. However, this method of manual detection resists accurate tumor detection and more time consuming. To overcome these problems, this paper uses computer aided techniques such as SVM for extraction of tumor is key component to automate specific radiological tasks for the characterization of anatomical structures and regions of interest and AD algorithm to locate tumor area on the MRI images. At the end of process, the tumor detected from the MR image and its exact position and the shape also determined. This technique allows the segmentation of brain tumor tissue with accuracy, improved performance and robustness; it also reduces the effect of noise. Key Words: MRI, Anisotrophic filtering ,SVM, Future Extraction,Segmentation,Processing