Lens-free on-chip 3D microscopy based on wavelength-scanning Fourier ptychographic diffraction tomography

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外文摘要：Lens-free on-chip microscopy is a powerful and promising high-throughput computational microscopy technique due to its unique advantage of creating high-resolution images across the full field-of-view(FOV)of the imaging sensor.Nevertheless,most current lens-free microscopy methods have been designed for imaging only two-dimensional thin samples.Lens-free on-chip tomography(LFOCT)with a uniform resolution across the entire FOV and at a subpixel level remains a critical challenge.In this paper,we demonstrated a new LFOCT technique and associated imaging platform based on wavelength scanning Fourier ptychographic diffraction tomography(wsFPDT).Instead of using angularly-variable illuminations,in wsFPDT,the sample is illuminated by on-axis wavelength-variable illuminations,ranging from 430 to 1200nm.The corresponding under-sampled diffraction patterns are recorded,and then an iterative ptychographic reconstruction procedure is applied to fill the spectrum of the three-dimensional(3D)scattering potential to recover the sample's 3D refractive index(RI)distribution.The wavelength-scanning scheme not only eliminates the need for mechanical motion during image acquisition and precise registration of the raw images but secures a quasi-uniform,pixel-super-resolved imaging resolution across the entire imaging FOV.With wsFPDT,we demonstrate the high-throughput,billion-voxel 3D tomographic imaging results with a half-pitch lateral resolution of 775 nm and an axial resolution of 5.43 μm across a large FOV of 29.85 mm2 and an imaging depth of＞200 μm.The effectiveness of the proposed method was demonstrated by imaging various types of samples,including micro-polystyrene beads,diatoms,and mouse mononuclear macrophage cells.The unique capability to reveal quantitative morphological properties,such as area,volume,and sphericity index of single cell over large cell populations makes wsFPDT a powerful quantitative and label-free tool for high-throughput biological applications.

作者：

Xuejuan Wu、Ning Zhou、Yang Chen、Jiasong Sun、Linpeng Lu、Qian Chen、Chao Zuo

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作者单位：

Smart Computational Imaging(SCI)Laboratory,Nanjing University of Science and Technology,No.200 Xiaolingwei Street,210094 Nanjing,Jiangsu,China

Smart Computational Imaging Research Institute(SCIRI)of Nanjing University of Science and Technology,210094 Nanjing,Jiangsu,China

Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense,No.200 Xiaolingwei Street,210094 Nanjing,Jiangsu,China

基金：

National Key Research and Development Program of ChinaNational Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaLeading Technology of Jiangsu Basic Research PlanYouth Foundation of Jiangsu ProvinceBiomedical Competition Foundation of Jiangsu ProvinceKey National Industrial Technology Cooperation Foundation of Jiangsu ProvinceFundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central UniversitiesFundamental Scientific Research Business Fee Funds for the Central UniversitiesOpen Research Fund of Jiangsu Key Laboratory of Spectral Imaging & Intelligent SenseOpen Research Fund of Jiangsu Key Laboratory of Spectral Imaging & Intelligent Sense

项目编号：

2022YFA12050022024YFE01013006210515162175109U21B20336222781862361136588BK20192003BK20210338BE2022847BZ202203930920032101309230102062023102001JSGP202105JSGP202201

出版年：

2024

DOI：

10.1038/s41377-024-01568-1

光:科学与应用(英文版)

中国科学院长春光学精密机械与物理研究所

光:科学与应用(英文版)

CSTPCD

ISSN：2095-5545

年,卷(期)：2024.13(9)