A survey on brain tumor diagnosis and edema detection based on machine learning

Early brain tumor diagnosis has a significant role in reducing the risk of disease, as well as led to get better treatment results. Usually, magnetic resonance imaging (MRI) images are evaluated manually through visual inspection, which is difficult, time-consuming and often erroneous;this process is performed by radiologists or clinical experts, and its accuracy depends on their experience. Recently, computer-aided diagnosis (CAD) becomes very essential to overcome these limitations. This paper provides a comprehensive assessment of the existing techniques and methodologies for automated detection of brain tumor coupled with oedema detection methods utilisation, with an emphasis on machine learning models. Moreover, this paper provides an analysis of the integrated procedure that pertains to the retrieval of brain pictures by identifying particular data sets in the procedure to recognise the stipulated attributes