Engineers have been actively developing tools to detect tumors and process medical imaging. Medical image segmentation is a powerful tool that is often used to detect tumors. Many scientists and researchers are working to develop and add more features to this tool. This project deals with the detection of brain tumors from MR images using a GUI interface in Matlab. Using the GUI, this program can use various segmentation combinations, filters and other image processing algorithms to achieve the best results. We started with filtering the image using Prewitt's horizontal edge emphasizing filter. The next step to detect the tumor is "basin pixels". The most important part of this project is that all Matlab programs work with "Matlab Guide" GUI. This allows us to use various combinations of filters and other imaging techniques to arrive at the best result that can help us to detect brain tumors in its early stages. Magnetic Resonance Imaging has become a widely used method of high quality medical imaging. Magnetic Resonance Imaging (MRI) is an advanced medical imaging technique that provides rich information about the anatomy of human soft tissue. Mathematical morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been widely applied to many applications such as edge detection, object segmentation, noise suppression and so on. Image Segmentation is used to extract various image features that can be merging or splitting in order to construct objects of interest in which analysis and interpretation can be performed. The article focuses on the detection of brain tumors and cancer cells from MR imaging using mathematical morphology.
Digital imaging is an emerging field in which doctors and surgeons are receiving different, easy pathways for the analysis of complex diseases such as cancer, brain tumor, breast cancer, kidney stones, etc. Detection of brain diseases is a very difficult task. Special care is taken for the segmentation of the image. A particular part of the body is scanned in the discussed applications of image analysis and techniques such as MRI], computed tomography, X-rays. The images are judged by doctors or surgeons to solve problems. Brain tumor is a major cause of disability and death worldwide and related abnormalities constitute major changes in life. A huge growth has been made in the last decade for the brain tumor in the region of brain cancer diagnosis. Brain cancer has been noticed that it is spreading all over the world and many universities and medical research university centers are focused on the subject. It can be understood with an example in the US, where 3000 children are brain-related diagnoses and brain tumors. Half of the children are dying at age 5 and leaving a fatal cancer in other children as well. The problem is more associated with neurological disabilities psychological problems, the delay leading the cause and the risk of death. It has been observed that Africans are having more chances of disease than other patients. In Tunisia, it is observed, for example, that cancer is the increase in mortality among the elderly responsible for 14.8% of deaths. After cardiovascular disease, the brain tumor is the second disease by which people are dying. The negative effect of the disease affects the economy of the country and society and disturbs both the family and the population. There are several tests, carried out on the patient to detect the cancer. Most commonly the test is Computerized Tomography (CT) and Magnetic Resonance Imaging (MRI), which are used to locate the brain tumor. The patient is influenced by the information obtained and the patient will receive. The widely used diagnostic technique is MRI. The classification and detection of the tumor is very expensive. MRI is an advanced technique for detecting brain cancer tissue and disease. Magnetic resonance imaging provides different information about different structures in the body that are achieved with the aid of an x-ray, computed tomography (CT), ultrasound, but MRI is the best technique for a higher quality of your images and has the advantage Of the lack of side effects in the tissues of the body.