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Multi-layer Born scattering: an efficient model for 3D phase tomography with multiple scattering objects (Conference Presentation)
Author(s): Michael Chen; Hsiou-Yuan Liu; David Ren; Laura Waller
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Paper Abstract

3D quantitative phase (refractive index) microscopy reveals volumetric structure of biological specimens. Optical diffraction tomography (ODT) is a common technique for 3D phase imaging. By angularly scanning a spatially coherent light source and measuring scattered fields on the imaging plane, 3D refractive index (RI) is recovered by solving an inverse problem. However, ODT often linearizes the process by using a weakly scattering model, e.g. the first Born approximation or Rytov approximation, which underestimate the RI and fail to reconstruct realistic shape of high RI contrast multiple scattering objects. On the other hand, non-linear models such as the multi-slice or beam propagation methods mitigate artifacts by modeling multiple scattering. However, they ignore back-scattering and intra-slice scattering and make a paraxial approximation by assuming each slice is infinitesimally thin. In this work, we propose a new 3D scattering model Multi-layer Born (MLB), which treats the object as thin 3D slabs with finite thickness and applies the first Born approximation on each slab as the field propagates through the object, increasing the accuracy significantly. In the meantime, a similar computation complexity is achieved comparing to the previously proposed multi-slice models. Therefore, MLB can achieve accuracy similar to that of FDTD or SEAGLE, a frequency domain solver, with orders of magnitude less computation time. In addition to forward scattering, multiple back-scattering effects are also captured by MLB unlike existing models. We apply MLB to recover the RI distribution of 3D phantoms and biological samples with intensity-only measurements from an LED array microscope and show that the results are superior to existing methods.

Paper Details

Date Published: 4 March 2019
Proc. SPIE 10883, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI, 108830I (4 March 2019); doi: 10.1117/12.2509977
Show Author Affiliations
Michael Chen, Univ. of California, Berkeley (United States)
Hsiou-Yuan Liu, Univ. of California, Berkeley (United States)
David Ren, Univ. of California, Berkeley (United States)
Laura Waller, Univ. of California, Berkeley (United States)

Published in SPIE Proceedings Vol. 10883:
Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XXVI
Thomas G. Brown; Tony Wilson, Editor(s)

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