Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

Shen, Che-Yung; Li, Jingxi; Mengu, Deniz; Ozcan, Aydogan

doi:10.1002/aisy.202300300

Title: Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

Journal Article · 24 August 2023 · Advanced Intelligent Systems

DOI: https://doi.org/10.1002/aisy.202300300 · OSTI ID:1996868

^[1]; Li, Jingxi ^[1];

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Electrical and Computer Engineering Department University of California Los Angeles CA 90 095 USA, Bioengineering Department University of California Los Angeles CA 90 095 USA, California NanoSystems Institute (CNSI) University of California Los Angeles CA 90 095 USA

As a label‐free imaging technique, quantitative phase imaging (QPI) provides optical path length information of transparent specimens for various applications in biology, materials science, and engineering. Multispectral QPI measures quantitative phase information across multiple spectral bands, permitting the examination of wavelength‐specific phase and dispersion characteristics of samples. Herein, the design of a diffractive processor is presented that can all‐optically perform multispectral quantitative phase imaging of transparent phase‐only objects within a snapshot. The design utilizes spatially engineered diffractive layers, optimized through deep learning, to encode the phase profile of the input object at a predetermined set of wavelengths into spatial intensity variations at the output plane, allowing multispectral QPI using a monochrome focal plane array. Through numerical simulations, diffractive multispectral processors are demonstrated to simultaneously perform quantitative phase imaging at 9 and 16 target spectral bands in the visible spectrum. The generalization of these diffractive processor designs is validated through numerical tests on unseen objects, including thin Pap smear images. Due to its all‐optical processing capability using passive dielectric diffractive materials, this diffractive multispectral QPI processor offers a compact and power‐efficient solution for high‐throughput quantitative phase microscopy and spectroscopy.

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Research Organization:: University of California, Los Angeles, CA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)

Grant/Contract Number:: SC0023088

OSTI ID:: 1996868

Journal Information:: Advanced Intelligent Systems, Journal Name: Advanced Intelligent Systems Journal Issue: 11 Vol. 5; ISSN 2640-4567

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: Germany

Language:: English

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36 MATERIALS SCIENCE
42 ENGINEERING
diffractive computing
diffractive networks
label-free imaging
multispectral imaging
optical processors
quantitative phase imaging

Title: Multispectral Quantitative Phase Imaging Using a Diffractive Optical Network

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