A computer‐aided approach for meningioma brain tumor detection using CANFIS classifier

Abnormal growth of cells in brain leads to the formation of tumors in brain. The earlier detection of the tumors in brain will save the life of the patients. Hence, this article proposes a computer‐aided fully automatic methodology for brain tumor detection using Co‐Active Adaptive Neuro Fuzzy Inference System (CANFIS) classifier. The internal region of the brain image is enhanced using image normalization technique and further contourlet transform is applied on the enhanced brain image for the decomposition with different scales. The grey level and heuristic features are extracted from the decomposed coefficients and these features are trained and classified using CANFIS classifier. The performance of the proposed brain tumor detection is analyzed in terms of classification accuracy, sensitivity, specificity, and segmentation accuracy.