Evidence map›Paper›PMID 40894552›Full record

ArticlebioRxiv : the preprint server for biology2025

Inverse-scattering in biological samples via beam-propagation.

Jeongsoo Kim, Blythe Bolton, Khashayar Moshksayan, Rishika Khanna, Mary E Swartz, Michał Ziemczonok, Mohini Kamra, Karin A Jorn, Sapun H Parekh, Małgorzata Kujawińska and 4 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Jeongsoo KimChandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0003-0965-0424
Blythe BoltonDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.
Khashayar MoshksayanWalker Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-5240-8193
Rishika KhannaWalker Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA.
Mary E SwartzDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.
Michał ZiemczonokWarsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland.ORCID 0000-0002-4802-1105
Mohini KamraDepartment of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0009-0004-2405-3120
Karin A JornPrecision One Health Initiative, University of Georgia, Athens, GA, USA.ORCID 0000-0002-2168-5809
Sapun H ParekhDepartment of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-8522-1854
Małgorzata KujawińskaWarsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland.ORCID 0000-0001-6521-6951
Johann EberhartDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-5258-2477
Elif Sarinay CenikDepartment of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0001-8514-5505
Adela Ben-YakarChandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0003-3468-6146
Shwetadwip ChowdhuryChandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA.ORCID 0000-0002-6142-0231

Funding

Mechanisms underlying the multifaceted basis of craniofacial dysmorphogenesisR35DE029086 · NIDCR · UNIVERSITY OF TEXAS AT AUSTIN · PI JOHANN K EBERHART · 2019 to 2026
$7.6M
Enhancing and expanding the CGC Strain CollectionP40OD010440 · OD · UNIVERSITY OF MINNESOTA · PI Aric L Daul, Ann E. Rougvie · 2012 to 2026
$7.5M
Genetic Screens in Zebrafish to Identify Gene-Ethanol InteractionsR01AA023426 · NIAAA · UNIVERSITY OF TEXAS AT AUSTIN · PI JOHANN K EBERHART · 2015 to 2026
$3.0M
Role of Nucleolus and Ribosomes in Organismal Growth and HomeostasisR35GM138340 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Elif Sarinay Cenik · 2020 to 2026
$2.4M
Characterizing the Genetics of FASD in Complementary Mouse and Fish ModelsR01AA031346 · NIAAA · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JOHANN K EBERHART, Scott Parnell · 2023 to 2026
$2.2M
Three-dimensional fluorescence imaging flow cytometry at up to million frames per secondR01GM148906 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI ADELA BEN-YAKAR · 2023 to 2026
$1.6M
Imaging deep-tissue morphogenesis at whole-organism scalesR35GM155424 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI Shwetadwip Chowdhury · 2024 to 2026
$1.0M
A Large-Scale Microfluidics Imaging Platform for High-Throughput Toxicity Testing using Canine Intestinal OrganoidsR43ES029890 · NIEHS · VIVOVERSE, LLC · PI HEGARTY, EVAN · 2019 to 2019
$223k
NIAAA NIH HHS R01 AA023426NIAAA NIH HHS R01 AA031346NIDCR NIH HHS R35 DE029086NIEHS NIH HHS R43 ES029890NIGMS NIH HHS R01 GM148906NIGMS NIH HHS R35 GM138340NIGMS NIH HHS R35 GM155424NIH HHS P40 OD010440
6 · The paper itself

Abstract

Multiple scattering limits optical imaging in thick biological samples by scrambling sample-specific information. Physics-based inverse-scattering methods aim to computationally recover this information, often using non-convex optimization to reconstruct the scatter-corrected sample. However, this non-convexity can lead to inaccurate reconstructions, especially in highly scattering samples. Here, we show that various implementation strategies for even the same inverse-scattering method significantly affect reconstruction quality. We demonstrate this using multi-slice beam propagation (MSBP), a relatively simple nonconvex inverse-scattering method that reconstructs a scattering sample's 3D refractive-index (RI). By systematically conducting MSBP-based inverse-scattering on both phantoms and biological samples, we showed that an amplitude-only cost function in the inverse-solver, combined with angular and defocus diversity in the scattering measurements, enabled high-quality, fully-volumetric RI imaging. This approach achieved subcellular resolution and label-free 3D contrast across diverse, multiple-scattering samples. These results lay the groundwork for robust use of inverse-scattering techniques to achieve biologically interpretable 3D imaging in increasingly thick, multicellular samples, introducing a new paradigm for deep-tissue computational imaging.

Identifiers

PMID40894552
PMCPMC12393416

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.