Date of Publication :2nd May 2018

Abstract: Image processing is used in most of the medical applications to diagnose wide variety of diseases. Brain tumor or neoplasm is the abnormal growth of tissues in brain and its surrounding regions. Image processing consists of preprocessing, segmentation and classification techniques which consists of methods for noise removal, feature extraction and morphological operations approach which helps in detecting and extracting the brain tumor from MRI images. In this way, MRI has become a useful medical diagnostic tool for detecting abnormalities in brain images. MRI provides better results than all other medical imaging tools. MR image is a sensitive tool in detecting the brain abnormalities such as tumors and infections during the early stage of the disease. Nowadays various applications are available for diagnosing the diseases from brain images. In our proposed method, a single system is used to detect various brain diseases such as birth defects in the brain, brain tumors and stroke. The abnormalities present in the MRI image are diagnosed based on some metric values. A region-based segmentation technique is used to extract the abnormalities such as brain tumors. A decision-based classification technique is also used which gives optimized results on detecting the range and type of abnormality from the brain images.

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