Using Hybrid Deep Learning, researchers in the scientific community have created a novel method for analyzing brain images taken as part of the Human Connectome Project. For the purpose of precise volumetric segmentation of brain tumors and tissues from MR images, the Aligned Cross-Modality Interaction Network (ACMINet) and APRNet have been presented as potential solutions. While APRNet delivers state-ofthe-art outcomes on benchmark datasets, ACMINet works to improve multi-modal features. DDSeg is a deep learning approach that improves accuracy and predicts tissue segmentation without the need for anatomical data and inter-modality registration. This is accomplished by learning tissue segmentation using high-quality imaging data that is obtained from the Human Connectome Project.