Classification of Brain Tumors Using Deep Features Extracted Using CNN

Abstract

Deep learning play a major role in medical automation, Convolutional Neural Networks (CNN) is an important machine learning technique for medical image segmentation and classification. In this work, we propose a novel approach that uses CNN-S for classifying brain tumors in to normal and three different types. The tumor is initially segmented from the MRI images using an enhanced ICA mixture mode model. From the segmented image deep features are extracted and classified. The results have been validated by measuring the performance of classifier on a data set available with Harvard Medical School.