Intracranial hemorrhage detection by 3D voxel segmentation on brain CT images

Intracranial hemorrhage (ICH) is a vital disease which occurs due to leakage or rupture of blood vessels within the brain tissue. In this paper, we propose a novel three-dimensional (3D) method for segmenting hemorrhage regions from a series of brain computed tomography (CT) images. This method combines a supervoxel approach for rough segmentation and three-dimensional graph cuts for refined segmentation. The main novelty of this method is to generalize traditional 2D segmentation of intracranial hemorrhage to a 3D approach, so that the intra-frame information of CT images is utilized to obtain better segmentation results. To evaluate the method, a brain CT database is built, which consists of 20 patients with intracranial hemorrhage at different sizes and locations. Experimental results demonstrate that the proposed approach provides segmentation which is similar to the manually labeled ground truth and outperforms existing 3D methods in accuracy and time-complexity.