Automated segmentation of brain tissues from Magnetic Resonance Imaging (MRI) scans is critical for scientific picture evaluation. It enhances the accuracy of anatomical segmentation, which in turn can be used to diagnose diverse neurological conditions. The segmentation procedure involves extracting gray remember, white count, and cerebrospinal fluid (CSF) from MRI photos. Automatic segmentation strategies use artificial intelligence (AI) algorithms to pick and segment distinctive mind tissues appropriately. Such techniques have the potential to significantly reduce the reliance on manual annotation, further rushing up the photo segmentation system. In this paper, we talk about numerous automatic segmentation strategies that employ machine getting-to-know and different AI paradigms, consisting of deep mastering, for the reason of brain tissue segmentation. We also discuss these segmentation techniques’ contemporary demanding situations and destiny directions.