Review of Brain Tumor Segmentation, Detection and Classification Algorithms in fMRI Images

Abstract

Nowadays Brain tumor detection in early stage is necessary because many people died due to unawareness of having a brain tumor. On the other side influence of machine learning becomes larger and larger in our lifes and our society, artificial intelligence might also start playing an important role in medical diagnosis and support of doctors and surgeons. This paper is focused on review of those papers which include segmentation, detection and classification of brain tumors. The common procedure for an algorithm which aims to classify brain tumors on fMRI or MRI scans is: Preprocessing the image for example by removing noise, then segmenting the image, which yields the region which might be a brain tumor, and finally classifying features such as inten-sity, shape and texture of this region. Many machine learning approaches towards brain tumor detection have already been made. However, these approaches, even though yielding good results, are not used yet. Therefore this research topic remains important and still requires attention.