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Reconstruction of Coronary Artery Centrelines from X-Ray Angiography Using a Mixture of Student's t-Distributions., , , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 291-299. (2016)Reconstruction of coronary arteries from X-ray angiography: A review., , , and . Medical Image Anal., (2016)Reconstruction of Coronary Trees from 3DRA Using a 3D+t Statistical Cardiac Prior., , , , and . MICCAI (2), volume 8674 of Lecture Notes in Computer Science, page 619-626. Springer, (2014)Group-wise similarity registration of point sets using Student's t-mixture model for statistical shape models., , , , and . Medical Image Anal., (2018)A Multi-resolution T-Mixture Model Approach to Robust Group-Wise Alignment of Shapes., , , , and . MICCAI (3), volume 9902 of Lecture Notes in Computer Science, page 142-149. (2016)Joint Clustering and Component Analysis of Spatio-Temporal Shape Patterns in Myocardial Infarction., , , , and . STACOM@MICCAI, volume 9534 of Lecture Notes in Computer Science, page 171-179. Springer, (2015)Reconstruction of coronary artery centrelines from X-ray rotational angiography using a probabilistic mixture model., , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97843A. SPIE, (2016)CoronARe: A Coronary Artery Reconstruction Challenge., , , and . CMMI/RAMBO/SWITCH@MICCAI, volume 10555 of Lecture Notes in Computer Science, page 96-104. Springer, (2017)Statistical shape modeling of the left ventricle: myocardial infarct classification challenge., , , , , , , , , and 26 other author(s). IEEE J Biomed Health Inform., 22 (2): 503--515 (February 2018)Training Deep Networks on Domain Randomized Synthetic X-ray Data for Cardiac Interventions., , , , , and . MIDL, volume 102 of Proceedings of Machine Learning Research, page 468-482. PMLR, (2019)