Academic Journal
Inverse scattering in biological samples via beam propagation.
| Τίτλος: | Inverse scattering in biological samples via beam propagation. |
|---|---|
| Συγγραφείς: | Kim J; Chandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA., Bolton B; Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA., Moshksayan K; Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA., Khanna R; Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA., Swartz ME; Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.; Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA., Ziemczonok M; Warsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland., Kamra M; Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA., Allenspach K; Precision One Health Initiative, University of Georgia, Athens, GA, USA., Parekh SH; Department of Biomedical Engineering, University of Texas at Austin, Austin, TX, USA., Kujawińska M; Warsaw University of Technology, Institute of Micromechanics and Photonics, Warsaw, Poland., Eberhart JK; Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.; Waggoner Center for Alcohol and Addiction Research, University of Texas at Austin, Austin, TX, USA., Sarinay Cenik E; Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA., Ben-Yakar A; Chandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA.; Walker Department of Mechanical Engineering, University of Texas at Austin, Austin, TX, USA., Chowdhury S; Chandra Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA. |
| Πηγή: | Science advances [Sci Adv] 2026 Aug 21; Vol. 12 (34), pp. eaec8678. Date of Electronic Publication: 2026 Aug 21. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: American Association for the Advancement of Science Country of Publication: United States NLM ID: 101653440 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2375-2548 (Electronic) Linking ISSN: 23752548 NLM ISO Abbreviation: Sci Adv Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Washington, DC : American Association for the Advancement of Science, [2015]- |
| Ιατρικοί όροι (MeSH): | Imaging, Three-Dimensional*/methods , Optical Imaging*/methods , Scattering, Radiation*, Image Processing, Computer-Assisted/methods ; Phantoms, Imaging ; Algorithms ; Animals ; Humans |
| Περίληψη: | Multiple scattering limits optical imaging in thick biological samples by scrambling sample-specific information. Physics-based inverse-scattering methods aim to computationally unscramble this information often by using nonconvex optimization solvers. However, their inherent nonconvexity often leads to highly sample-dependent performance and inaccurate reconstructions, particularly in strongly scattering specimens. Here, we introduce a novel inverse-scattering framework based on multislice beam propagation (MSBP) that robustly achieves high-quality scatter correction and label-free volumetric imaging across a diverse range of scattering biological samples. We rigorously benchmarked imaging performance across multiple MSBP solver implementations using both scattering calibration phantoms and biological specimens. We found that an amplitude-only cost function in the inverse solver, combined with angular and defocus diversity in the scattering measurements, enabled volumetric, label-free imaging with high-quality and subcellular-level scatter correction. Together, these results establish a foundation for the reliable application of inverse scattering to achieve biologically interpretable three-dimensional imaging in increasingly thick, multicellular samples, thus introducing a new paradigm for deep-tissue computational imaging. |
| Σχόλια: | Update of: bioRxiv. 2025 Aug 22:2025.08.17.670744. doi: 10.1101/2025.08.17.670744.. (PMID: 40894552) |
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| Grant Information: | R35 GM155424 United States GM NIGMS NIH HHS; P40 OD010440 United States OD NIH HHS; R43 ES029890 United States ES NIEHS NIH HHS; R01 GM148906 United States GM NIGMS NIH HHS; R35 GM138340 United States GM NIGMS NIH HHS; R35 DE029086 United States DE NIDCR NIH HHS; R01 AA023426 United States AA NIAAA NIH HHS; R01 AA031346 United States AA NIAAA NIH HHS |
| Entry Date(s): | Date Created: 20260821 Date Completed: 20260821 Latest Revision: 20260825 |
| Update Code: | 20260825 |
| PubMed Central ID: | PMC13496197 |
| DOI: | 10.1126/sciadv.aec8678 |
| PMID: | 42627909 |
| Βάση Δεδομένων: | MEDLINE |
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