{
  "abstract": "Multimodal fluorescence and phase imaging provides complementary information about biological samples. However, existing simultaneous fluorescence-phase techniques primarily operate in transmission mode and are limited to thin specimens, restricting their use in thick tissues and in vivo applications. Although multiphoton microscopy enables deep-tissue fluorescence imaging, combining it with three-dimensional refractive-index (RI) imaging remains challenging because few methods can reconstruct the RI of bulky, label-free tissues in reflection mode at subcellular resolution. Here, we introduce fluorescence-illuminated diffraction tomography (FDT), which reconstructs the 3D RI of label-free and fluorescence-labeled objects from diffracted fluorescence images acquired in reflection mode under two-photon excitation. FDT uses the transport of intensity equation and a self-supervised neural network based on explicit neural fields. Compared with state-of-the-art implicit neural fields, this approach improves computational speed, reconstruction accuracy, and interpretability. We demonstrate FDT in two experimental regimes: reconstructing the 3D RI of label-free tissues up to 300 μ m thick placed on a fluorescent substrate, and reconstructing the 3D RI of fluorescence-labeled, 3D-cultured cells without transmission-side access using fluorescence emitted by the cells themselves. FDT establishes a foundation for accessible reflection-mode multimodal fluorescence-phase imaging in complex biological systems.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "name": "Renzhi He",
      "orcid": "0000-0003-1837-4062"
    },
    {
      "name": "Yucheng Li"
    },
    {
      "name": "Junjie Chen"
    },
    {
      "name": "Truc M. Dinh"
    },
    {
      "name": "Charlotte R. Stevens"
    },
    {
      "name": "Aidan E. Gilchrist",
      "orcid": "0000-0003-3536-1044"
    },
    {
      "name": "Yi Xue",
      "orcid": "0000-0003-2622-083X"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/55eynancg1vfn.bib",
  "cited_by": 1,
  "doi": "10.1038/s41467-026-78326-x",
  "fulltext_url": null,
  "id": "55eynancg1vfn",
  "issns": [
    "2041-1723"
  ],
  "landing_url": "https://www.nature.com/articles/s41467-026-78326-x",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3107|Digital Holography and Microscopy"
    ]
  ],
  "openalex": "W7221308322",
  "pdf_url": "https://www.nature.com/articles/s41467-026-78326-x_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-10",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/55eynancg1vfn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:38Z",
      "native_id": "10.1038/s41467-026-78326-x",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41467-026-78326-x"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "openalex:3107|Digital Holography and Microscopy",
      "subfield": "amo"
    }
  ],
  "title": "Fluorescence-illuminated diffraction tomography using explicit neural fields",
  "title_text": "Fluorescence-illuminated diffraction tomography using explicit neural fields",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:38Z",
  "url": "https://research.draconitic.com/paper/55eynancg1vfn",
  "venue": "Nature Communications",
  "versions": []
}