TY - GEN
T1 - A multi-resolution multi-model method for coronary centerline extraction based on minimal path
AU - Jia, Dengqiang
AU - Shi, Wenzhe
AU - Rueckert, Daniel
AU - Liu, Liu
AU - Ourselin, Sebastien
AU - Zhuang, Xiahai
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2016.
PY - 2016
Y1 - 2016
N2 - Extracting centerlines of coronary arteries is challenging but important in clinical applications of cardiac computed tomography angiography (CTA). Since manual annotation of coronary arteries is time-consuming, laborintensive and subject to intra- and inter-variations, we propose a new method to fully automatically extract the coronary centerlines. We first develop a new image filter which generates pixels with salient vessel features within a given window. This filter hence can capture sparsely distributed but important vessel points, enabling the minimal path (MP) process to track the key centerline points at different resolution of the images. Then, we reformulate the filter for multi-resolution fast marching, which not only can speed up the coronary tracking process, but also can help the front propagation to step over the indistinct segments of the coronary artery such as at the locations of stenosis. We embed this scheme into the MP framework to develop a multi-resolution multi-model approach (MMP), where the extracted centerlines from low-resolution MP serve as prior and constraints for the high-resolution process. We evaluated the performance of this method using the Rotterdam CTA training data and the coronary artery algorithm evaluation framework. The average inside of our extraction was 0.51 mm and the overlap was 72.9 %. The mean runtime on the original resolution CTA images was 3.4 min using the MMP method.
AB - Extracting centerlines of coronary arteries is challenging but important in clinical applications of cardiac computed tomography angiography (CTA). Since manual annotation of coronary arteries is time-consuming, laborintensive and subject to intra- and inter-variations, we propose a new method to fully automatically extract the coronary centerlines. We first develop a new image filter which generates pixels with salient vessel features within a given window. This filter hence can capture sparsely distributed but important vessel points, enabling the minimal path (MP) process to track the key centerline points at different resolution of the images. Then, we reformulate the filter for multi-resolution fast marching, which not only can speed up the coronary tracking process, but also can help the front propagation to step over the indistinct segments of the coronary artery such as at the locations of stenosis. We embed this scheme into the MP framework to develop a multi-resolution multi-model approach (MMP), where the extracted centerlines from low-resolution MP serve as prior and constraints for the high-resolution process. We evaluated the performance of this method using the Rotterdam CTA training data and the coronary artery algorithm evaluation framework. The average inside of our extraction was 0.51 mm and the overlap was 72.9 %. The mean runtime on the original resolution CTA images was 3.4 min using the MMP method.
UR - http://www.scopus.com/inward/record.url?scp=84984844767&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-43775-0_29
DO - 10.1007/978-3-319-43775-0_29
M3 - Conference contribution
AN - SCOPUS:84984844767
SN - 9783319437743
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 320
EP - 328
BT - Medical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings
A2 - Liao, Hongen
A2 - Zheng, Guoyan
A2 - Lee, Su-Lin
A2 - Cattin, Philippe
A2 - Jannin, Pierre
PB - Springer Verlag
T2 - 7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016
Y2 - 24 August 2016 through 26 August 2016
ER -