Cimen S, Unberath M, Frangi A, Maier A (2017)
Publication Type: Conference contribution
Publication year: 2017
Publisher: Springer Verlag
Book Volume: 10555 LNCS
Pages Range: 96-104
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Quebec City, QC, CAN
ISBN: 9783319675633
DOI: 10.1007/978-3-319-67564-0_10
CoronARe ranks state-of-the-art methods in symbolic and tomographic coronary artery reconstruction from interventional C-arm rotational angiography. Specifically, we benchmark the performance of the methods using accurately pre-processed data, and study the effects of imperfect pre-processing conditions (segmentation and background subtraction errors). In this first iteration of the challenge, evaluation is performed in a controlled environment using digital phantom images, where accurate 3D ground truth is known.
APA:
Cimen, S., Unberath, M., Frangi, A., & Maier, A. (2017). CoronARe: A coronary artery reconstruction challenge. In M. Jorge Cardoso, Tal Arbel (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 96-104). Quebec City, QC, CAN: Springer Verlag.
MLA:
Cimen, Serkan, et al. "CoronARe: A coronary artery reconstruction challenge." Proceedings of the 5th International Workshop on Computational Methods for Molecular Imaging, CMMI 2017, 2nd International Workshop on Reconstruction and Analysis of Moving Body Organs, RAMBO 2017 and 1st International Stroke Workshop on Imaging and Treatment Challenges, SWITCH 2017 held in Conjunction with 20th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2017, Quebec City, QC, CAN Ed. M. Jorge Cardoso, Tal Arbel, Springer Verlag, 2017. 96-104.
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