An atlas-based deep brain structure segmentation method: from coarse positioning to fine shaping

Abstract

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 structure by-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 pro posed method has been applied on a publicly available MRI brain database and can achieve comparatively high segmentation accuracy.