  Automatic liver segmentation plays an important role in computer-aided
diagnosis and treatment. Manual segmentation of organs is a difficult and
tedious task and so prone to human errors. In this paper, we propose an
adaptive 3D region growing with subject-specific conditions. For this aim we
use the intensity distribution of most probable voxels in prior map along with
location prior. We also incorporate the boundary of target organs to restrict
the region growing. In order to obtain strong edges and high contrast, we
propose an effective contrast enhancement algorithm to facilitate more accurate
segmentation. In this paper, 92.56% Dice score is achieved. We compare our
method with the method of hard thresholding on Deeds prior map and also with
the majority voting on Deeds registration with 13 organs.
