Computer-aided System Of The Liver Vessels Visualization Based On Dynamic Enhanced CT Images

The application of Image segmentation and visualization of organs is a hot research topic in the medical domain, which could provide the detailed visualization information of patients such as inner structures for the doctor in making the surgery planning. Currently, the technologies of segmentation and visualization for the organs such as the bones, the lung and the brain have been well developed while there is little literature for the segmentation and visualization of the largest organ in human body—the liver. In this paper, we present the algorithms for hepatic vasculature segmentation, three-dimensional reconstruction and visualization from dynamic contrast-enhanced CT image series based on inherent gray and geometric characteristic of tubular structure. The main contents of the paper are listed as follows:1) The algorithm for the segmentation of hepatic vasculature is presented based on the priori knowledge and morphological filtering. As a result, the volume data of hepatic vasculature from dynamic contrast-enhanced CT image series have been obtained by region growing arithmetic;2) The tubular model of hepatic vasculature is proposed in reference to its inherent characteristic to realize the three-dimensional reconstruction;3) The multi-branching vascular tree model of hepatic vasculature is skeletonized with all branch nods marked;4) The computer-assisted visualization system of hepatic vasculature is proposed and implemented based on the above-mentioned algorithms.The results of the reconstruction of hepatic vasculature show that the hepatic vasculature, such as the left hepatic vein, the right hepatic vein, the middle hepatic vein and especially inner minute blood vessels, are high-visible with distinct gradation. Consequently, the accurate segmentation of hepatic vasculature can be realized from the algorithms for hepatic vasculature segmentation based on the priori knowledge, region growing arithmetic and morphological filtering. Meanwhile the precise vascular segmentation and the high efficiency of vascular skeletonization can be achieved due to the three-dimensional reconstruction based on the tubular model of hepatic vasculature. In addition, the geometric information of hepatic vasculature can be visualized, and at the same time the comparison of vascular segments can also be easily reconstructed with the assistance of the marking of skeletonized nods as well as the defining of the vascular geometric properties such as the subordinate and hierarchical relationship of vasculature.