TY - GEN
T1 - An Open-Source End-to-End Pipeline for Generating 3D+t Biventricular Meshes from Cardiac Magnetic Resonance Imaging
AU - Dillon, Joshua R.
AU - Mauger, Charlène
AU - Zhao, Debbie
AU - Deng, Yu
AU - Petersen, Steffen E.
AU - McCulloch, Andrew D.
AU - Young, Alistair A.
AU - Nash, Martyn P.
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
PY - 2025
Y1 - 2025
N2 - Increased interest in digital-twin based healthcare has stimulated recent advancements in personalised biventricular modelling from cardiac magnetic resonance (CMR) imaging. However, there remains no publicly available end-to-end pipeline for generating structured meshes of the heart across the entire cardiac cycle. This paper presents a new pipeline and tests it on CMR data contributed from two centres. The proposed pipeline comprises view classification, segmentation of the left and right ventricular chambers and myocardium, contour generation, and model fitting in a fully automated sequence, requiring only an image directory as input. The use of 3D U-Nets was explored, and found to increase the temporal coherence of resulting meshes compared to 2D U-Nets when evaluated on 10 test cases. The pipeline is available to be deployed across various applications, including digital-twin based simulations, statistical shape and motion analyses, and clinical research. The pipeline—including code, models, and documentation—can be accessed at https://github.com/UOA-Heart-Mechanics-Research/biv-me.
AB - Increased interest in digital-twin based healthcare has stimulated recent advancements in personalised biventricular modelling from cardiac magnetic resonance (CMR) imaging. However, there remains no publicly available end-to-end pipeline for generating structured meshes of the heart across the entire cardiac cycle. This paper presents a new pipeline and tests it on CMR data contributed from two centres. The proposed pipeline comprises view classification, segmentation of the left and right ventricular chambers and myocardium, contour generation, and model fitting in a fully automated sequence, requiring only an image directory as input. The use of 3D U-Nets was explored, and found to increase the temporal coherence of resulting meshes compared to 2D U-Nets when evaluated on 10 test cases. The pipeline is available to be deployed across various applications, including digital-twin based simulations, statistical shape and motion analyses, and clinical research. The pipeline—including code, models, and documentation—can be accessed at https://github.com/UOA-Heart-Mechanics-Research/biv-me.
KW - Biventricular modelling
KW - CMR
KW - Open-source
UR - https://www.scopus.com/pages/publications/105009756619
U2 - 10.1007/978-3-031-94562-5_34
DO - 10.1007/978-3-031-94562-5_34
M3 - Conference contribution
AN - SCOPUS:105009756619
SN - 9783031945618
T3 - Lecture Notes in Computer Science
SP - 372
EP - 383
BT - Functional Imaging and Modeling of the Heart - 13th International Conference, FIMH 2025, Proceedings
A2 - Chabiniok, Radomír
A2 - Zou, Qing
A2 - Hussain, Tarique
A2 - Nguyen, Hoang H.
A2 - Zaha, Vlad G.
A2 - Gusseva, Maria
PB - Springer Science and Business Media Deutschland GmbH
T2 - 13th International Conference on Functional Imaging and Modeling of the Heart, FIMH 2025
Y2 - 1 June 2025 through 5 June 2025
ER -