IHF-Harmony: Multi-Modality Magnetic Resonance Images Harmonization using Invertible Hierarchy Flow Model

• URL: http://arxiv.org/abs/2602.21536v1
• Date: Wed, 25 Feb 2026 03:46:12 GMT
• Title: IHF-Harmony: Multi-Modality Magnetic Resonance Images Harmonization using Invertible Hierarchy Flow Model
• Authors: Pengli Zhu, Yitao Zhu, Haowen Pang, Anqi Qiu,
• Abstract summary: Retrospective MRI harmonization is limited by poor scalability across modalities and reliance on traveling subject datasets.<n>IHF-Harmony is a unified invertible hierarchy flow framework for multi-modality harmonization using unpaired data.<n> Experiments across multiple MRI modalities demonstrate that IHF-Harmony outperforms existing methods in both anatomical fidelity and downstream task performance.
• Score: 3.4718032510023438
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Retrospective MRI harmonization is limited by poor scalability across modalities and reliance on traveling subject datasets. To address these challenges, we introduce IHF-Harmony, a unified invertible hierarchy flow framework for multi-modality harmonization using unpaired data. By decomposing the translation process into reversible feature transformations, IHF-Harmony guarantees bijective mapping and lossless reconstruction to prevent anatomical distortion. Specifically, an invertible hierarchy flow (IHF) performs hierarchical subtractive coupling to progressively remove artefact-related features, while an artefact-aware normalization (AAN) employs anatomy-fixed feature modulation to accurately transfer target characteristics. Combined with anatomy and artefact consistency loss objectives, IHF-Harmony achieves high-fidelity harmonization that retains source anatomy. Experiments across multiple MRI modalities demonstrate that IHF-Harmony outperforms existing methods in both anatomical fidelity and downstream task performance, facilitating robust harmonization for large-scale multi-site imaging studies. Code will be released upon acceptance.

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