REVIEW ON AUTOMATIC PROCESSING OF BRAIN IMAGES FOR SEGMENTATION AND ABNORMALITY DETECTION
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 11, Pages 217-221
AbstractBrain tumour detection is very popular in the area of medical image processing. This is due to the sensitivity of brain functionality and inter structure. Any kind of ignorance towards the problems related with brain may cause serious impact on human life/life style. Therefore, early detection or diagnosis of abnormalities or tumours helps the doctors and patients to rectify the brain related health problems. The images are obtained through scanning techniques which are very common. Images obtained from the scanning needs to be segmented carefully for the future analysis and damage control procedures. In this paper, a detailed review on different types of segmentation techniques proposed by various authors is studied and compared for a clear understanding of existing segmentation techniques. They are tabulated to summarize different methodologies, segmentation techniques, and existing processes for further studies on Brain image segmentation. Finally, a brief understanding towards deep learning techniques is studied in this paper to understand their role in modern era for automated segmentation process.
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