Advancing Precision Medicine: An Exploration of Hybrid Deep Learning Approaches for Automated Human Brain Tissue Segmentation and Tumour Localization in MRI Imaging

This study aims to revolutionize medical image analysis by combining hybrid deep learning techniques to automate human brain tissue segmentation and tumour localization in MRI images. Traditional methods struggle with the complexity and variability of brain structures, necessitating a more adaptive approach. The proposed framework combines Convolutional Neural Networks, Recurrent Neural Networks, and attention mechanisms to improve the model’s ability to recognize fine-grained details and spatial dependencies. The model’s performance will be measured against cutting-edge methodologies, highlighting the potential for increased diagnostic accuracy and reduced reliance on manual intervention. The anticipated outcomes include a robust automated tool for clinicians, which will speed up brain MRI scan analysis and allow for more accurate identification of pathological regions.