Inverse scattering in biological samples via beam propagation

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.

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Publication Details

Journal
Science Advances
Published
2026-08-21
DOI
https://doi.org/10.1126/sciadv.aec8678
Citations
2
Primary Topic
Digital Holography and Microscopy
Type
article
Field-Weighted Citation Impact
9.72

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article

Inverse scattering in biological samples via beam propagation

Adela Ben‐Yakar, Mary E. Swartz, Khashayar Moshksayan, Rishika Khanna et al.
2 citations
Science Advances
Digital Holography and Microscopy
9.72
article

Inverse scattering in biological samples via beam propagation

Adela Ben‐Yakar, Mary E. Swartz, Khashayar Moshksayan, Rishika Khanna, Elif Sarinay Cenik, Johann K. Eberhart, Shwetadwip Chowdhury, Sapun H. Parekh, Małgorzata Kujawińska, Mohini Kamra, Michał Ziemczonok, Blythe Bolton, Jeongsoo Kim
article en
2 citations

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.

Science AdvancesVol. 12(34)
Warsaw University of Technology (PL), University of Georgia (US), Walker (United States) (US), The University of Texas at Austin (US)
Welch Foundation, Chan Zuckerberg Initiative, Politechnika Warszawska, National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism, National Institute of General Medical Sciences, National Institute of Environmental Health Sciences, National Institute of Dental and Craniofacial Research
Openalex Percentile: Top 4%
Digital Holography and Microscopy
9.72
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