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  • Received: May. 9, 2019

    Accepted: Nov. 9, 2019

    Posted: Dec. 31, 2019

    Published Online: Dec. 31, 2019

    The Author Email: Li Jiaji (, Matlock Alex (, Li Yunzhe (, Chen Qian (, Zuo Chao (, Tian Lei (

    DOI: 10.1117/1.AP.1.6.066004

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    Jiaji Li, Alex Matlock, Yunzhe Li, Qian Chen, Chao Zuo, Lei Tian. High-speed in vitro intensity diffraction tomography[J]. Advanced Photonics, 2019, 1(6): 066004

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Advanced Photonics, Vol. 1, Issue 6, 066004 (2019)

High-speed in vitro intensity diffraction tomography 

Jiaji Li1,†, Alex Matlock2, Yunzhe Li2, Qian Chen1, Chao Zuo1,*, and Lei Tian2,*

Author Affiliations

  • 1Nanjing University of Science and Technology, School of Electronic and Optical Engineering, Nanjing, Jiangsu, China
  • 2Boston University, Department of Electrical and Computer Engineering, Boston, Massachusetts, United States


We demonstrate a label-free, scan-free intensity diffraction tomography technique utilizing annular illumination (aIDT) to rapidly characterize large-volume three-dimensional (3-D) refractive index distributions in vitro. By optimally matching the illumination geometry to the microscope pupil, our technique reduces the data requirement by 60 times to achieve high-speed 10-Hz volume rates. Using eight intensity images, we recover volumes of ~350 μm × 100 μm × 20 μm, with near diffraction-limited lateral resolution of ~ 487 nm and axial resolution of ~ 3.4 μm. The attained large volume rate and high-resolution enable 3-D quantitative phase imaging of complex living biological samples across multiple length scales. We demonstrate aIDT’s capabilities on unicellular diatom microalgae, epithelial buccal cell clusters with native bacteria, and live Caenorhabditis elegans specimens. Within these samples, we recover macroscale cellular structures, subcellular organelles, and dynamic micro-organism tissues with minimal motion artifacts. Quantifying such features has significant utility in oncology, immunology, and cellular pathophysiology, where these morphological features are evaluated for changes in the presence of disease, parasites, and new drug treatments. Finally, we simulate the aIDT system to highlight the accuracy and sensitivity of the proposed technique. aIDT shows promise as a powerful high-speed, label-free computational microscopy approach for applications where natural imaging is required to evaluate environmental effects on a sample in real time.


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