Novel Mechanism of Classifying the Brain Tumor for Identifying its Critical State

Classification of brain tumor is one of the most challenging tasks in the clinical and radiological research. Upon investigating the existing research contribution, we find that still there is wide open scope of addressing classification problem pertaining to brain tumor. Therefore, this manuscript presents a simple mechanism of classifying the brain tumor in order to categorize its state of criticality. The proposed system applies a multi-level preprocessing to enhance the input image followed by image thresholding for feature extraction and decomposition using wavelet transform. The extracted features are further subjected to process of dimensional reduction that maintains a balance between good number of enriched feature and less size of redundant feature using statistical approach. Further, a supervised learning approach is implemented that further optimizes the classification process. The study outcome is further benchmarked with different process of classification to show the efficient computational environment of proposed system.