MRI is important for diagnosing brain tumors due to its clear imaging. Manual brain tissue segmentation in MRI images is time- consuming and prone to errors. Deep learning can now automate this task effectively. Left4Dead team uses deep learning to segment brain tissues and identify tumor locations in MRI scans accurately. CNNs, RNNs, and other deep learning structures combined with traditional techniques enhance segmentation performance. Applying hybrid deep learning methods in medical imaging may improve brain tumor detection. Techniques like merging features on different scales and transfer learning can tackle obstacles in brain tissue segmentation and tumor detection. Integration of GANs and reinforcement learning can enhance data augmentation in this field. This review analyzes advanced techniques and challenges in previous research.