MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstruction

• URL: http://arxiv.org/abs/2603.03710v1
• Date: Wed, 04 Mar 2026 04:25:32 GMT
• Title: MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstruction
• Authors: Seunghoi Kim, Chen Jin, Henry F. J. Tregidgo, Matteo Figini, Daniel C. Alexander,
• Abstract summary: MPFlow is a zero-shot multi-modal reconstruction framework built on rectified flow.<n>It incorporates auxiliary MRI modalities at inference time without retraining the generative prior to improve anatomical fidelity.
• Score: 8.702496582146042
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Zero-shot MRI reconstruction relies on generative priors, but single-modality unconditional priors produce hallucinations under severe ill-posedness. In many clinical workflows, complementary MRI acquisitions (e.g. high-quality structural scans) are routinely available, yet existing reconstruction methods lack mechanisms to leverage this additional information. We propose MPFlow, a zero-shot multi-modal reconstruction framework built on rectified flow that incorporates auxiliary MRI modalities at inference time without retraining the generative prior to improve anatomical fidelity. Cross-modal guidance is enabled by our proposed self-supervised pretraining strategy, Patch-level Multi-modal MR Image Pretraining (PAMRI), which learns shared representations across modalities. Sampling is jointly guided by data consistency and cross-modal feature alignment using pre-trained PAMRI, systematically suppressing intrinsic and extrinsic hallucinations. Extensive experiments on HCP and BraTS show that MPFlow matches diffusion baselines on image quality using only 20% of sampling steps while reducing tumor hallucinations by more than 15% (segmentation dice score). This demonstrates that cross-modal guidance enables more reliable and efficient zero-shot MRI reconstruction.

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