Automated medical image classification using deep learning

Medical imaging is extremely important in the domain of medicine. Image classification now utilized to distinguish aberrant tissues from healthy tissue brain imaging. The tumor identified MRI images by using some techniques, where area as well size detected. Automatic detection efficient and time- saving, assisting neurologists diagnosis. Tumors can increase risk cancer, which most common cause death or major mortality worldwide. To detect tumors at moment, effective automation essential. Marker based Watershed algorithm a typical segmentation technique used for identifying tumors. For detection, we performed marker watershed on with use gray scale images, then noise removal morphological operations. steps methodology are follows: Gray-level sharpening was pre-processing, image segmented thresholding algorithm, CNN classifying images. Finally, tumor's location were determined.