A literature review is described on cerebrum (brain) tumor diagnosis. The aim of this survey is to provide an outline for those who are new to the field of image processing, and also to provide a reference for those searching for literature in these applications. Tumor is because of an abnormal development of cells (tissues) inside the brain. Magnetic Resonance Imaging (MRI), Computer Tomography (CT) imaging techniques are used for early detection of abnormal changes in tumor tissues or cells. Its correct detection and identification at an early stage is the only way to get cure. Brain tumor tissues may become malignant (cancerous) if not diagnosed at right time. A recent couple of years various image processing algorithms have been proposed for correct and efficient computer aided diagnosis of cerebrum tumors. An algorithm effectively works on CT, MRI images. It is been observed that an automatic segmentation method using Convolution Neural Network (CNN) with 3*3 kernels provide deeper architecture and positive results against over fitting. Watershed segmentation algorithm removes the salt & pepper noise without disturbing edges. It is very easy for automatic and accurate calculation of tumor area. Sobel edge detection based improved edge detection algorithm provide superior performance over conventional segmentation algorithm K-Mean algorithm used
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