对腹部CT序列图像肝脏、脾脏以及肾脏的同步自动分割和综合分析是腹部疾病诊断、术前规划与指导的重要前提。针对单时相CT序列因信息量不足使得多器官同时自动分割不准确的问题，提出基于多时相的4D图割算法。首先结合解剖学先验模型和多时相CT图像本征信息，构建4D图割能量函数，然后根据多时相CT序列目标器官亮度特征，定位种子区域，实现基于4D图割的多器官同时鲁棒自动分割。根据肝脏分割结果，结合肝序列图像的二维纹理信息和三维体数据信息建立特征空间，运用反向传播神经网络和水平集演化方法对已分割出的肝脏进行血管提取，建立血管三维显示系统，并对肝动脉、门静脉和肝静脉进行识别。本项目研究可解决腹部多器官的体积测量、三维重建、疾病诊断、手术导航、器官移植以及肝脉管识别与分析等所需的关键技术问题，有助于医师及时方便地同时获取腹部多器官(组织)的整体信息和三维显示，为计算机辅助诊断和疾病治疗提供技术支持和决策服务。

The simultaneous automatic segmentation and comprehensive analysis of liver, spleen and kidneys from abdominal CT series are the important prerequisite for abdominal diseases diagnosis, pre-operative planning and guidance. Aiming at the inaccurate automatic segmentation of multiple organs because of the insufficient information from single phase CT series, the project proposes a multiphase-based 4D graph cuts algorithm for the automatic segmentation of abdominal multiple organs from multiphase CT series. Firstly, combining the anatomy prior models and the intrinsic information of multiphase CT series, this project constructs the energy function of 4D graph cuts, and then based on the brightness characteristics of target organs from the multiphase abdominal CT series, locates the seed regions of the target organs, and realizes the simultaneous robust automatic segmentation of multiple organs from abdominal CT series based on 4D graph cuts. Next, this project constructs the feature vector space for the liver series obtained from the 4D graph cuts algorithm by combining the 2D texture information and the 3D voxel information of the liver series, and extracts liver blood vessels from the segmented liver series using back-propagation neural network and level set evolution method, and constructs 3D liver vascular visualization system, where the hepatic artery, the hepatic portal vein and the hepatic vein are distinguished, respectively. This project aims at the the key technologies for abdominal multiple organs of volume measurement, 3D reconstruction, diseases diagnosis, surgical navigation, organ transplantation, and liver vascular recognition and analysis, which help the radiologists and clinicians timely and easily get the overall information and 3D visualization of abdominal multiple organs (tissues) simultaneously, and provide the technical supports and decision-making services for computer-aided diagnosis and diseases treatment.