Chain of Flow: ECG-Conditioned 4D Cardiac Cine Generation from Patient-Specific Anatomical Anchor
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Abstract (arXiv)
Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be directly available at the point of analysis. We introduce Chain of Flow (COF), an electrocardiography (ECG)-conditioned framework that combines patient-specific MRI and current ECG for subject-specific 4D cardiac cine generation. On the UK Biobank dataset, COF achieves strong image-level fidelity and downstream function-oriented performance on a shared same-visit evaluable benchmark. Multi-slice and multi-resolution analyses indicate stable structural generation quality across the short-axis stack and heterogeneous acquisition resolutions. Controlled phase-robustness analyses across resampled input MRI phases further provide same-visit proxy support for patient-specific MRI plus current ECG when a target MRI phase is not directly observed. A cross-visit route provides exploratory serial evidence, with the clearest gains in current-facing region-of-interest readout. Disease-category functional audits, case-level volume-trajectory evidence review further delineate where the current patient-specific MRI plus ECG formulation remains stable for anatomy-aware downstream cardiac analysis. Code is available at https://anonymous.4open.science/r/COF-paper-release-C88B.
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References · 17
- 2018VoxelMorph: A Learning Framework for Deformable Medical Image Registrationcited by 657
- 2022MONAI: An open-source framework for deep learning in healthcarecited by 438
- 2018Generative Adversarial Network in Medical Imaging: A Reviewcited by 257
- 2024Improving the Training of Rectified Flowscited by 106
- 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogramcited by 84
- 2022SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generationcited by 56
- 2018Joint Learning of Motion Estimation and Segmentation for Cardiac MR Image Sequencescited by 47
- 2023Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesiscited by 32
- 2023Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inferencecited by 18
- 2024EchoNet-Synthetic: Privacy-preserving Video Generation for Safe Medical Data Sharingcited by 17
- 2023Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imagingcited by 14
- 2024Solving the Inverse Problem of Electrocardiography for Cardiac Digital Twins: A Surveycited by 14
5 more
- 2021Physics-constrained Deep Learning for Robust Inverse ECG Modelingcited by 12
- 2018Factorised spatial representation learning: application in semi-supervised myocardial segmentationcited by 11
- 2024ECHOPulse: ECG controlled echocardio-grams video generationcited by 8
- 2025CardiacFlow: 3D+t Four-Chamber Cardiac Shape Completion and Generation via Flow Matchingcited by 8
- 2019Bayesian Optimization on Large Graphs via a Graph Convolutional Generative Model: Application in Cardiac Model Personalizationcited by 6
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