Trending in the recent days is the field of Medical Image Processing which is a rapidly growing and competitive field. Medical Image methodologies are utilized for Medical detection and treatment of diseases. One such critical and life endangering disease, is Brain Tumour which is an abnormal growth of brain cells inside the brain. Identification of brain tumour is a challenge due to the complications in the structure of brain. Functional Magnetic Resonance Images (FMRI) is beneficial for providing the detailed information about human soft tissue anatomy, which is in turn, is helpful in diagnosis of brain tumour. Basically, there are different stages which are involved in the detection of brain tumour such as image pre-processing, segmentation, feature extraction and classification. The intention of this research work is rendering a detailed overview for FMRI-based brain tumour segmentation and classification techniques. First, a concise introduction to brain tumours is furnished and then the imaging modalities of brain tumours are provided. Afterwards, Image pre-processing is conducted as a first step on FMR images of the affected patients to improve the features of brain cells. Second, introduction of state of the art methods of FMRI-based brain tumour segmentation is done. In addition, discussion on the assessment and establishment of the results of FMRI-based brain tumour classification are provided. As a last step, anon-subjective evaluation is submitted and developments in the futurity and to be in vogue are dealt for FMRI-based brain tumours segmentation and classification techniques. © 2017 Elsevier B.V., All rights reserved.