Chen Kun, Zhang Yong, Pohl Kilian, Syeda-Mahmood Tanveer, Song Zhihuan, Wong Stephen T C
State Key Laboratory of Industrial Control Technology, Institute of Industrial Process Control, Zhejiang University, Hangzhou, China.
Annu Int Conf IEEE Eng Med Biol Soc. 2010;2010:3133-7. doi: 10.1109/IEMBS.2010.5627192.
Automatic or semi-automatic segmentation and tracking of artery trees from computed tomography angiography (CTA) is an important step to improve the diagnosis and treatment of artery diseases, but it still remains a significant challenging problem. In this paper, we present an artery extraction method to address the challenge. The proposed method consists of two steps: (1) a geometric moments based tracking to secure a rough centerline, and (2) a fully automatic generalized cylinder structure-based snake method to refine the centerlines and estimate the radii of the arteries. In this method, a new line direction based on first and second order geometric moments is adopted while both gradient and intensity information are used in the snake model to improve the accuracy. The approach has been evaluated on synthetic images as well as 8 clinical coronary CTA images with 32 coronary arteries. Our method achieves 94.7% overlap tracking ability within an average distance inside the vessel of 0.36 mm.
从计算机断层血管造影（CTA）中自动或半自动分割和跟踪动脉树是改善动脉疾病诊断和治疗的重要步骤，但它仍然是一个极具挑战性的问题。在本文中，我们提出了一种动脉提取方法来应对这一挑战。所提出的方法包括两个步骤：（1）基于几何矩的跟踪以确定大致的中心线，以及（2）基于全自动广义圆柱体结构的蛇形方法来细化中心线并估计动脉半径。在该方法中，采用了基于一阶和二阶几何矩的新线方向，同时在蛇形模型中使用梯度和强度信息以提高准确性。该方法已在合成图像以及包含32条冠状动脉的8幅临床冠状动脉CTA图像上进行了评估。我们的方法在血管内平均距离0.36毫米的情况下实现了94.7%的重叠跟踪能力。
