Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.
Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography.
复制标题
DOI：
10.1007/s10554-011-9894-2
复制
发表时间：
2012-04
期刊：
影响因子：
--
通讯作者：
Dijkstra J
中科院分区：
文献类型：
--
作者：
Yang G;Kitslaar P;Frenay M;Broersen A;Boogers MJ;Bax JJ;Reiber JH;Dijkstra J
冠状动脉计算机断层扫描血管造影术（CCTA）是一种用于心脏和冠状动脉可视化的无创成像模式。为了充分利用CCTA数据集的潜力并将其应用于临床实践，需要一种自动冠状动脉提取方法。本文的目的是提出并验证一种全自动的CCTA图像中的冠状动脉中心线提取算法。该算法是基于一个改进版本的Frangi的血管性过滤器，删除不必要的步骤边缘响应的心脏腔室的边界。基于这种新的血管性过滤器，冠状动脉提取管道自动提取主分支和侧分支的中心线。该算法首先使用MICCAI冠状动脉跟踪挑战2008（CAT 08）中使用的名为鹿特丹冠状动脉算法评价框架的标准化评价框架进行评价。它包括128条手动划定的参考中心线。我们的方法的平均重叠和准确度分别为93.7%和0.30 mm，与CAT08中提出的其他五种自动方法相比，分别排名第一和第三位。其次，在50个临床数据集中，从横向平面中的管腔轮廓生成总共100条参考中心线，这些参考中心线由心脏科专家手动校正。在该评价中，平均重叠和准确度分别为96.1%和0.33 mm。在标准台式计算机上，一个数据集的整个处理时间不到2分钟。总之，我们新开发的自动方法可以提取冠状动脉CCTA图像具有良好的性能，在提取能力和准确性。
Coronary computed tomographic angiography (CCTA) is a non-invasive imaging modality for the visualization of the heart and coronary arteries. To fully exploit the potential of the CCTA datasets and apply it in clinical practice, an automated coronary artery extraction approach is needed. The purpose of this paper is to present and validate a fully automatic centerline extraction algorithm for coronary arteries in CCTA images. The algorithm is based on an improved version of Frangi’s vesselness filter which removes unwanted step-edge responses at the boundaries of the cardiac chambers. Building upon this new vesselness filter, the coronary artery extraction pipeline extracts the centerlines of main branches as well as side-branches automatically. This algorithm was first evaluated with a standardized evaluation framework named Rotterdam Coronary Artery Algorithm Evaluation Framework used in the MICCAI Coronary Artery Tracking challenge 2008 (CAT08). It includes 128 reference centerlines which were manually delineated. The average overlap and accuracy measures of our method were 93.7% and 0.30 mm, respectively, which ranked at the 1st and 3rd place compared to five other automatic methods presented in the CAT08. Secondly, in 50 clinical datasets, a total of 100 reference centerlines were generated from lumen contours in the transversal planes which were manually corrected by an expert from the cardiology department. In this evaluation, the average overlap and accuracy were 96.1% and 0.33 mm, respectively. The entire processing time for one dataset is less than 2 min on a standard desktop computer. In conclusion, our newly developed automatic approach can extract coronary arteries in CCTA images with excellent performances in extraction ability and accuracy.
登录
查看更多内容
影响因子：
10.6
作者：
Xu, CY;Prince, JL
通讯作者：
Prince, JL
影响因子：
4.4
作者：
Wesarg, Stefan;Khan, M. Fawad;Firle, Evelyn A.
通讯作者：
Firle, Evelyn A.
影响因子：
10.9
作者：
Schaap, Michiel;Metz, Coert T.;van Walsum, Theo;van der Giessen, Alina G.;Weustink, Annick C.;Mollet, Nico R.;Bauer, Christian;Bogunovic, Hrvoje;Castro, Carlos;Deng, Xiang;Dikici, Engin;O'Donnell, Thomas;Frenay, Michel;Friman, Ola;Hernandez Hoyos, Marcela;Kitslaar, Pieter H.;Krissian, Karl;Kuehnel, Caroline;Luengo-Oroz, Miguel A.;Orkisz, Maciej;Smedby, Orjan;Styner, Martin;Szymczak, Andrzej;Tek, Hueseyin;Wang, Chunliang;Warfield, Simon K.;Zambal, Sebastian;Zhang, Yong;Krestin, Gabriel P.;Niessen, Wiro J.
通讯作者：
Niessen, Wiro J.
影响因子：
10.9
作者：
Friman, Ola;Hindennach, Milo;Peitgen, Heinz-Otto
通讯作者：
Peitgen, Heinz-Otto
DOI：
10.1007/bfb0056195
发表时间：
1998-01-01
期刊：
MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI'98
影响因子：
--
作者：
Frangi, AF;Niessen, WJ;Viergever, MA
通讯作者：
Viergever, MA