Detection and Extraction of Brain Tumor from MRI Images Using K-Means Clustering and Watershed Algorithms

Medical imaging is generally equated to radiology or "clinical imaging" and the medical practitioner responsible for interpreting (and sometimes acquiring) the image is a radiologist. Diagnostic radiography designates the technical aspects of medical imaging and in particular the acquisition of medical images. The radiographer or radiologic technologist is usually responsible for acquiring medical images of diagnostic quality, although some radiological interventions are performed by radiologists. Brain tumor is a disease, which is a common, chronic, systemic, autoimmune inflammatory disease in nature that mainly affects the human body; there are two main types of tumors: malignant or cancerous tumors and benign tumors. Cancerous tumors can be divided into primary tumors that started within the brain and those that spread from somewhere else known as brain metastasis tumors. This article deals mainly with tumors that start within the brain. All types of brain tumors may produce symptoms that vary depending on the part of the brain involved. These may include headaches, seizures, problem with vision, vomiting, and mental changes. The headache is classically worst in the morning and goes away with vomiting. More specific problems may include difficulty in walking, speaking and with sensation. As the disease progresses unconsciousness may occur. In this research work we have extracted and detected brain tumor using two different techniques. Simulation will be done on MALTAB from original brain tumor images from Clinical Laboratory.