An atlas-based deep brain structure segmentation method: from coarse positioning to fine shaping
Segmentation of deep brain structures is a challenging task for MRI images due to blurry structure boundaries, small object size and irregular shapes. In this paper, we present a new atlas-based segmentation method. It first uses a prior spatial dependency tree to constrain the relative positions between different deep brain structures and determine an optimal sequence for the structureby-structure segmentation. After positioning the structures, the segmentation result is further fine tuned by a non-rigid registration procedure between the atlas image and the target image using the histogram of the gradient magnitudes lying on the structure boundaries. The proposed method has been applied on a publicly available MRI brain database and can achieve comparatively high segmentation accuracy.