Accurate segmentation of CMF bones from MRI is one of the most important fundamental steps in clinical applications, and it can also be used in other areas, such as character animation and assistive robotics. In this paper, we propose a cascade framework based on the recently well-received and prominent deep learning methods. Specifically, we first propose a 3D fully convolutional network architecture for a coarse segmentation of the bone tissue. Further, we propose to utilize CNN for fine-grained level segmentation around the predicted bone tissue area. The conducted experiments show that our proposed 3D deep learning model could achieve good performance in terms of segmentation accuracy.