OSCR

Gigavoxel-scale multiple-scattering-aware lensless holotomography.

Overview

Authors: Mikołaj Rogalski1, Julianna Winnik1, Julia Dudek1, Piotr Arcab1, Emilia Wdowiak1, Paweł Matryba2,3, Marzena Stefaniuk2, Piotr Zdańkowski1, Maciej Trusiak1
ORCID iDs: Mikołaj Rogalski, Julianna Winnik, Julia Dudek, Piotr Arcab, Emilia Wdowiak, Paweł Matryba, Marzena Stefaniuk, Piotr Zdańkowski, Maciej Trusiak
  1. Warsaw University of Technology, Institute of Micromechanics and Photonics, Faculty of Mechatronics,Warsaw, Poland
  2. Laboratory of Neurobiology, Nencki Institute of Experimental Biology of Polish Academy of Sciences,Warsaw, Poland
  3. Department of Immunology, Medical University of Warsaw,Warsaw, Poland
Institutions: Warsaw University of Technology (Poland); Polish Academy of Sciences (Poland); Medical University of Warsaw (Poland)
Journal: Light, science & applications, volume 15, issue 1, article 381
Dates: received 11 September 2025; accepted 23 June 2026; published online 16 September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1038/s41377-026-02416-0 · PMID 42744785 · PMCID PMC13578224 · OpenAlex W4416551562
Open access: gold, a free copy (OpenAlex)
Preprint: arxiv:2508.00567
Status: data only
Categories: histology / microscopy (modality)
Keywords: Imaging and sensing, Optical metrology, Phase-contrast microscopy, Interference microscopy, Biophotonics
Topic: Digital Holography and Microscopy (Atomic and Molecular Physics, and Optics, Physics and Astronomy), according to OpenAlex
Funding: EC | EU Framework Programme for Research and Innovation H2020 | H2020 Priority Excellent Science | H2020 European Research Council (H2020 Excellent Science - European Research Council) (101117392)
Citations: not cited yet (Europe PMC); 50 references in the paper

Abstract

Holotomography (HT) has revolutionized quantitative label-free 3D imaging, yet conventional lens-based implementations are fundamentally constrained in field-of-view (FOV) and imaging depth, limiting their utility for critical high-throughput applications in material and life sciences. Lensless HT (LHT) offers a promising alternative for large-volume examination, however existing approaches fail to accurately reconstruct highly scattering samples over extended depths, which remains a critical challenge in optical imaging field. Here, we introduce a gigavoxel-scale, multiple-scattering-aware LHT with a large FOV (surpassing 0.6 cm2), millimeter-scale axial range, and pixel level (~2.4 µm) resolution. Our approach leverages a multi-wavelength, oblique-illumination hologram reconstruction and a robust, automatic illumination angle calibration, which are necessary for precise large-volume 3D holographic reconstruction. Moreover, we propose optimization-driven multi-slice tomographic framework to accurately capture multiple scattering effects outperforming first order Born/Rytov-based inversions. To rigorously validate our method, we reconstruct bespoke multi-layer two-photon polymerized test structure over a 1.7 mm imaging depth and 25 mm2 FOV, yielding an unprecedented 3D space-bandwidth product exceeding a gigavoxel level. Furthermore, we demonstrate for the first time on-chip label-free imaging of entire 500-µm-thick tissue slice of optically cleared mouse brain. With the proposed method, we aim to unlock powerful new capabilities for large-scale, quantitative, label-free 3D imaging across biomedicine, neuroscience, material sciences and beyond.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data, not to its authors' code: see the Data section.

Code availability

The algorithms used in this study are provided as part of the Supplementary Information.

Reproduced under the paper's license (CC BY), from the paper cited above.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none, so it has no map.

Data

Datasets cited

Data availability

The raw data supporting the findings of this study, including all hologram series used in Figs. 2, S2, 3, 4, 5, are available at Zenodo: https://doi.org/10.5281/zenodo.18771332.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 5 keywords, 1 funder, 47 references.

Cite

This paper

Rogalski, M., Winnik, J., Dudek, J., Arcab, P., Wdowiak, E., Matryba, P., Stefaniuk, M., Zdańkowski, P., & Trusiak, M. (2026). Gigavoxel-scale multiple-scattering-aware lensless holotomography. Light, science & applications, 15(1), 381. https://doi.org/10.1038/s41377-026-02416-0

BibTeX

@article{rogalski2026gigavoxel,
author = {Rogalski, Mikołaj and Winnik, Julianna and Dudek, Julia and Arcab, Piotr and Wdowiak, Emilia and Matryba, Paweł and Stefaniuk, Marzena and Zdańkowski, Piotr and Trusiak, Maciej},
title = {{Gigavoxel-scale multiple-scattering-aware lensless holotomography}},
journal = {Light, science \& applications},
year = {2026},
month = sep,
volume = {15},
number = {1},
pages = {381},
publisher = {Nature Publishing Group},
issn = {2095-5545},
doi = {10.1038/s41377-026-02416-0},
url = {https://doi.org/10.1038/s41377-026-02416-0},
pmid = {42744785},
pmcid = {PMC13578224}
}

RIS

TY - JOUR
AU - Rogalski, Mikołaj
AU - Winnik, Julianna
AU - Dudek, Julia
AU - Arcab, Piotr
AU - Wdowiak, Emilia
AU - Matryba, Paweł
AU - Stefaniuk, Marzena
AU - Zdańkowski, Piotr
AU - Trusiak, Maciej
TI - Gigavoxel-scale multiple-scattering-aware lensless holotomography
T2 - Light, science & applications
J2 - Light Sci Appl
PY - 2026
DA - 2026/09/16
VL - 15
IS - 1
SP - 381
SN - 2095-5545
PB - Nature Publishing Group
DO - 10.1038/s41377-026-02416-0
UR - https://doi.org/10.1038/s41377-026-02416-0
LA - en
ER -

CSL-JSON

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