中文摘要：

为提高肝脏分割效率、改善分割效果，针对传统Fast Marching（FM）方法固定参数值r对肝脏分割结果的影响，提出了一种改进的FM肝脏分割方法。根据对腹部CT图像序列的肝脏区域灰度统计信息，估算出每幅图像上肝脏区域大小，进而自适应调整FM中的到达时间参数T，有效消除传统的固定参数值对分割效率和准确率的影响。对10套腹部CT图像序列的实验结果表明，该方法能够全自动、快速、准确的分割出肝脏区域。其中，处理单副CT图像所需的平均时间为0．3s，平均准确率为97％，其高效性、准确性为临床诊断和手术导航提供了有利信息。

英文摘要：

For the sake of high accuracy and efficiency of liver segmentation, we propose an improved Fast Marching method based on self-adaptive parameter adjustment. The arrival time parameter T is adjusted according to the intensity statistics of the liver region on set of abdominal CT images, which can used to estimate the size of liver region on the eorre-spomling CT slices. This method is efficient for elimination the influence of traditional same parameter values on the efficiency and accuracy of liver segmentation. When tested on 10 sets of abdominal CT images, experimental results show that the proposed approach can segment liver automatically, quickly and accurately. The average time for processing a slice of CT image resulted to be 0.3s, and the average accuracy is up to 97%. It is accurate and efficient enough for the use in clinical diagnosis and surgical navigation.