{
  "abstract": "Magnetic resonance imaging (MRI) exhibits substantial scanner and protocol dependent appearance variations, making harmonization challenging without distorting patient specific anatomy, particularly in abdominal imaging. We propose AC-Diff, an anatomy--contrast disentangled diffusion framework that formulates MRI harmonization as a factor-specific generative intervention. Using aligned multi-contrast supervision and cross-patient factor swapping, AC-Diff learns to separate anatomical structure from acquisition-dependent contrast. Unlike conventional image or latent diffusion, AC-Diff restricts stochastic generation to the contrast subspace while the source anatomy bypasses diffusion and is directly reused during reconstruction. Experiments on an in-house multi-vendor cohort and the external Duke Liver MRI dataset demonstrate improved target-domain alignment with strong structural preservation. In downstream liver segmentation, AC-Diff improves Dice from 0.942 for the original inputs to 0.954 for the harmonized images. These results support contrast-specific latent generation as a promising approach to anatomy-preserving MRI harmonization.",
  "abstract_shown": true,
  "affiliations": [
    "University of Texas Health Sciences Center at Houston"
  ],
  "article_type": "New results",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "H. Feng"
    },
    {
      "name": "H. Dang"
    },
    {
      "name": "L. You"
    },
    {
      "name": "H. Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "X. Zhou"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9fddgb1f0ckhc.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.09.28.755033",
  "fulltext_url": "https://www.biorxiv.org/content/10.64898/2026.09.28.755033v1.full",
  "id": "9fddgb1f0ckhc",
  "issns": [],
  "landing_url": "https://www.biorxiv.org/content/10.64898/2026.09.28.755033v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "biorxiv",
      "bioengineering"
    ],
    [
      "openalex",
      "2741|Advanced MRI Techniques and Applications"
    ]
  ],
  "openalex": "W7214722756",
  "pdf_url": "https://www.biorxiv.org/content/10.64898/2026.09.28.755033v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/9fddgb1f0ckhc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:11Z",
      "native_id": "10.64898/2026.09.28.755033",
      "source": "biorxiv",
      "url": "https://www.biorxiv.org/content/10.64898/2026.09.28.755033v1"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "biorxiv:bioengineering",
      "subfield": "systems-synthetic"
    }
  ],
  "title": "AC-Diff: Anatomy-Contrast Disentangled Diffusion for Multi-Vendor Liver MRI Harmonization",
  "title_text": "AC-Diff: Anatomy-Contrast Disentangled Diffusion for Multi-Vendor Liver MRI Harmonization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:11Z",
  "url": "https://research.draconitic.com/paper/9fddgb1f0ckhc",
  "venue": "bioRxiv",
  "versions": []
}