Abstract
A tumor is an abnormal tissue in the brain that damages the cell’s ability to operate. Hence, detecting a brain tumor is a difficult undertaking. Manual tumor identification is dangerous since it necessitates the insertion of a needle into the brain. As a result, automated brain tumor detection technologies are required. Medical image processing gives fundamental information about brain abnormalities and assists doctors in making the best treatment decisions. Early detection and treatment reduce the odds of cancer worsening, enhances the survival rate, and improves the chances of a healthy life. In this work, enhancement of brain tumor MRI (‘Magnetic Resonance Imaging’) and therefore, better detection of the tumor present, if any. This paper proposes blending of existing algorithms like BBHE (‘Bi-histogram Equalisation’), CLAHE (‘Contrast Limited Adaptive Histogram Equalisation’), RESIHE (‘Recursive Exposure-based Sub-Image Histogram Equalisation’), MSRCR (‘Multi Scale Retinex with Colour Restoration’) and more. Out of the ones that were experimented, CLAHE + MSRCR performed better; it’s BRISQUE (‘Blind/Reference less Image Spatial Quality Evaluator’) value was found to be 29.805718 which shows the tumor is better visible.
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