BRAIN CANCER CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 9, Pages 1476-1485
AbstractA program has been planned and developed to diagnose and identify brain cancer. The program employs computer-based techniques in the detections of tumor fragments or tumors, and in photographs of various Astrocytoma brain tumor patients, it classifies the type of tumor utilizing Artificial Neural Network. For the diagnosis of the brain tumor, photographs of the patients afflicted by cancer were created utilizing image processing technique such as imaging segmentation,histogram equalization, image enhancement, morphologic surgery and feature extraction.Gray Level Co-occurrence Matrix (GLCM) is used for the detection of surface characteristics in the observed tumor. Such properties are contrasted with the functionality contained in the knowledge base.To order to identify various forms of brain cancers, a neuro fuzzy concept was eventually created. The entire system was verified in two stages: first, the phase of learning / training as well as second, the phase of recognition / testing.The device was equipped through documented MRI images from patients with impaired brain cancer from the Department of Radiology of Tata Memorial Hospital (TMH). Known brain cancer tests of impacted MRI scans are often obtained from TMH and used for device monitoring. The method has been shown to be effective in classifying these samples.
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