Multi-Modal Brain Tumor Segmentation Model to solve Mutual Inhibition between Modes

Abstract

Medical image segmentation has become a key research area in the machine learning community with brain tumor segmentation as one of the most challenging problems in the field. Brain tumor segmentation using machine learning models can help in diagnosing, treating, and monitoring of brain tumors which would significantly improve the medical care of patients. The aim of this research is to develop a network that could solve the problem of mutual inhibition in multi-modal image segmentation for brain tumors. Specifically, multi-modal image segmentation represents the true day-to-day scenario of brain tumor imaging which will be automated using machine learning networks. Contribution to the multi-modal brain tumor segmentation problem will allow for the fast detection and classification of brain tumors which will lead to improved medical care to patients.