Gülsün M Akif, Tek Hüseyin
Imaging and Visualization, Siemens Corporate Research, Princeton, NJ, USA.
Med Image Comput Comput Assist Interv. 2008;11(Pt 1):602-11. doi: 10.1007/978-3-540-85988-8_72.
In this paper, we present a novel method for extracting center axis representations (centerlines) of blood vessels in contrast enhanced (CE)-CTA/MRA, robustly and accurately. This graph-based optimization algorithm which employs multi-scale medialness filters extracts vessel centerlines by computing the minimum-cost paths. Specifically, first, new medialness filters are designed from the assumption of circular/elliptic vessel cross-sections. These filters produce contrast and scale independent responses even the presence of nearby structures. Second, they are incorporated to the minimum-cost path detection algorithm in a novel way for the computational efficiency and accuracy. Third, the full vessel centerline tree is constructed from this optimization technique by assigning a saliency measure for each centerline from their length and radius information. The proposed method is computationally efficient and produces results that are comparable in quality to the ones created by experts. It has been tested on more than 100 coronary artery data set where the full coronary artery trees are extracted in 21 seconds in average on a 3.2 GHz PC.
在本文中，我们提出了一种在对比增强（CE）-CTA/MRA中稳健且准确地提取血管中心线表示（中心线）的新方法。这种基于图的优化算法采用多尺度中值滤波器，通过计算最小成本路径来提取血管中心线。具体而言，首先，从圆形/椭圆形血管横截面的假设出发设计新的中值滤波器。即使存在附近结构，这些滤波器也能产生与对比度和尺度无关的响应。其次，为了提高计算效率和准确性，它们以一种新颖的方式被纳入到最小成本路径检测算法中。第三，通过根据每条中心线的长度和半径信息为其分配显著性度量，利用这种优化技术构建完整的血管中心线树。所提出的方法计算效率高，生成的结果在质量上与专家创建的结果相当。它已经在100多个冠状动脉数据集上进行了测试，在一台3.2 GHz的个人电脑上，平均21秒就能提取出完整的冠状动脉树。
