术前风险量化分析是确保肝切除手术成功的关键，而肝脏体积测量和储备功能状态评估是精准肝切除手术风险分析的重要因素。本项目拟由肝脏CT图像的灰度特性和结构特性出发，提出一种自适应Fast Marching（FM）方法进行病变及剧烈形变肝脏的轮廓提取，进而估算肝脏和病变组织的体积信息，并借助虚拟手术切除技术，测算拟切除肝脏的体积信息；研究Child分级和吲哚菁绿（ICG）肝脏储备功能测定结果与肝切除量之间的关系，构建肝脏储备功能的综合评估模型；最后，结合肝脏体积测量信息和肝脏储备功能综合评估，构建精准肝切除手术风险量化模型。项目的研究成果，将对精准肝切除技术的发展具有重要推动作用，同时对肝脏外科的解剖教学、科研及临床手术治疗水平提高具有重要的科学意义和应用价值。

Preoperative risk analysis is the key to ensure the success of liver surgery. The volume measurement and the comprehensive assessment of liver reserve function are important factors in accurate risk analysis of hepatic surgery. According to the intensity and structural feature of liver on CT images, the project is planned to propose an adaptive Fast Marching (FM) method for the contour extraction of the lesions and the severe deformation of liver, which can be used to obtain accurate volume information of liver and lesion. And we use the virtual surgical technology to access the volume information of liver resection. Then, we study on the relationship between Child grade, indocyanine green (ICG) and the volume of liver resection, building a comprehensive evaluation model of the liver reserve function. Finally, combining with the liver volume measurement information and the comprehensive assessment of liver reserve function, we build a risk quantification model for precision liver resection surgery. The research results of this project will motivate the development of precision liver resection technology. And it also has important scientific significance and application value on liver surgical teaching, research and improvement of clinical surgery level.