FlowMoDL: Model-Based Deep Learning with Conjugate-Gradient Data Consistency for Highly Accelerated 4D Flow MRI Reconstruction

arXiv:2608.25828 · cs.CV, cs.LG · Submitted 2026-08-26 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/tgottwald/FlowMoDL

Project page: https://cmrxrecon.github.io/2026/data.html

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Consistency — 18× in this paper · explained in 3 episodes
• Angular Error — 9× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Regularization — 4× in this paper · explained in 3 episodes
• Alignment — 1× in this paper · explained in 1 episode
• Fidelity — 1× in this paper · explained in 2 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Multi-Layer Perceptron — 1× in this paper
• Over-smoothing — 1× in this paper · explained in 4 episodes

Sources

• FlowMRI-Net: A Generalizable Self-Supervised 4D Flow MRI Reconstruction network
• Decoupled Weight Decay Regularization

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