International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056 Volume: 02 Issue: 02 | May-2015 www.irjet.net p-ISSN: 2395-0072 © 2015, IRJET.NET- All Rights Reserved Page 191 BRAIN TUMOR DETECTION IN MEDICAL IMAGING USING MATLAB Pankaj Kr. Saini 1 , Mohinder Singh 2 1 M. Tech Scholar, Department of Computer Science & Engineering, Maharishi Ved Vyas Engineering College Jagadhri, Yamuna Nagar, India 2 Assistant Professor, Department of Computer Science & Engineering, Maharishi Ved Vyas Engineering College Jagadhri, Yamuna Nagar India Abstract: Magnetic Resonance Imaging has become a widely used method of high quality medical imaging. Magnetic resonance imaging (MRI) is an advanced medical imaging technique providing rich information about the human soft tissue anatomy. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been applied widely to many applications such as edge detection, object segmentation, noise suppression and so on. Image Segmentation is used to extract various features of the image which can be merger or split in order to build objects of interest on which analysis and interpretation can be performed. The paper focuses on the detection of brain tumor and cancer cells of MRI Images using mathematical morphology. Keywords: Magnetic resonance imaging (MRI), Image segmentation, Digital Image Processing (DIP) 1. INTRODUCTION Digital Image processing [1] is an emerging field in which doctors and surgeons are getting different easy pathways for the analysis of complex disease such as cancer, brain tumor, breast cancer, kidney stones, etc. The detection of brain disease [2, 4] is a very challenging task, in which special care is taken for image segmentation. A particular part of body is scanned in the discussed applications of the image analysis and techniques such as MRI [2, 3], CT scan, X rays. The images are judged by physicians or surgeons to solve the problems. Brain tumor is a big cause of disability and death worldwide and related abnormalities constitute for major changes in life. A tremendous growth has been done in the last decade for brain tumor in the region of cerebral cancer diagnosis. Cerebral cancer [5] has been noticed that is spreading over the world and many colleges and university medical research centers are focusing on the issue. It can be understand with an example in US, in which 3000 children are facing the brain related diagnosis and brain tumors. Half of the children are dying at the age of 5 years and leaving a fatal cancer in other children too. The problem is more associated with neurological disabilities psychological problems, retardation that is leading the cause and risk of death. It has been noticed that African are having more chances of disease than other patients. In Tunisia, it is noticed for instance, that the cancers is mortality increasing among the elderly responsible for 14.8% of deaths. After cardiovascular diseases brain tumor is the second disease by which people are dying. The negative effect of the disease effects the economy of the country and society and disturb the family as well as and a high burden for the nation. There are several tests, conducted on the patient to detect the cancer. Most commonly test is Computed Tomography (CT) [1, 4] and Magnetic Resonance Imaging (MRI), which are used to locate brain tumor. The patient is influenced by the Information obtained and the patient will receive. The widely used diagnosis technique is MRI. The classification and detection of the tumor [6] is very expensive. MRI is an advance technique to detect the tissues and the disease of brain cancer. MRI provides the different information about different structures in the body which are achieved with the help of an X-ray, computed tomography (CT) scan, Ultrasound but MRI is the best technique for higher quality of its images and has the advantage of lack of side effects on the body tissues. MRI technology has a magnetic field and train pulses of radio wave energy that makes pictures of structures and organs within a body. Moreover, the amount of the resultant data is analyzed too much manually. It constitutes the effective use of MRI images as main hurdle and obligates the effective application of computer aided automatic or semiautomatic methods [6] to analyze the product images. In the diagnosis analysis of MRI images, segmentation of image is required and analysis of image segmentation is very important part of any type of detection in image analysis. Image segmentation [1, 7] techniques help to get the meaningful