Development of segmentation algorithms for brain tumor detection and classification using mr images and performance analysis

This work introduces an optimized deep learning mechanism; named Dolphin-SCA based Deep CNN, to improve the accuracy and to make effective decisions in classification. Initially, the input MR images are given to the pre-processing and then, subjected to the segmentation process. The segmentation process is carried out using a fuzzy GVF deformable hybrid model with Dolphin Echolocation based Sine Cosine algorithm (Dolphin-SCA). Then, the feature extraction process is performed based on power LBP and statistical features, like mean, variance, and skewness.