High-resolution 3D refractive index microscopy of multiple-scattering samples from intensity images
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Abstract (arXiv)
Optical diffraction tomography (ODT) reconstructs a samples volumetric refractive index (RI) to create high-contrast, quantitative 3D visualizations of biological samples. However, standard implementations of ODT use interferometric systems, and so are sensitive to phase instabilities, complex mechanical design, and coherent noise. Furthermore, their reconstruction framework is typically limited to weakly-scattering samples, and thus excludes a whole class of multiple-scattering samples. Here, we implement a new 3D RI microscopy technique that utilizes a computational multi-slice beam propagation method to invert the optical scattering process and reconstruct high-resolution (NA>1.0) 3D RI distributions of multiple-scattering samples. The method acquires intensity-only measurements from different illumination angles, and then solves a non-linear optimization problem to recover the sample 3D RI distribution. We experimentally demonstrate reconstruction of samples with varying amounts of multiple scattering: a 3T3 fibroblast cell, a cluster of C. elegans embryos, and a whole C. elegans worm, with lateral and axial resolutions of 250 nm and 900 nm, respectively.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Aug 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 1; 2025: 2; 2026: 1.
9 papers.
- 2021Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fieldscited by 48
- 2023Single View Refractive Index Tomography with Neural Fieldscited by 8
- 2021Physical model simulator-trained neural network for computational 3D phase imaging of multiple-scattering samplescited by 3
- 2022Physics-informed neural networks for diffraction tomographycited by 2
- 2025Double Blind Imaging with Generative Modelingcited by 1
- 2025Neural Inverse Scattering with Score-based Regularizationcited by 1
- 2022Optical Diffraction Tomography based on 3D Physics-Inspired Neural Network (PINN)cited by 0
- 2024WaveOrder: A differentiable wave-optical framework for scalable biological microscopy with diverse modalitiescited by 0
- 2026Inductively Scalable, Single-Step Neural Surrogates for Wave-Scattering Inverse Problemscited by 0
- 2026Inductively Scalable, Single-Step Neural Surrogates for Wave-Scattering Inverse Problems18 Aug 2026
- 2025Neural Inverse Scattering with Score-based Regularization20 May 2025
- 2025Double Blind Imaging with Generative Modeling27 Mar 2025
- 2024WaveOrder: A differentiable wave-optical framework for scalable biological microscopy with diverse modalities13 Dec 2024
- 2023Single View Refractive Index Tomography with Neural Fields8 Sep 2023
- 2022Physics-informed neural networks for diffraction tomography28 Jul 2022
- 2022Optical Diffraction Tomography based on 3D Physics-Inspired Neural Network (PINN)10 Jun 2022
- 2021Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields27 Nov 2021
- 2021Physical model simulator-trained neural network for computational 3D phase imaging of multiple-scattering samples29 Mar 2021