Increasing a Microscope’s Effective Field of View via Overlapped Imaging and Machine Learning

Xing Yao; Haoran Xi; Kevin C. Zhou; Amey Chaware; Colin Cooke; Yuting Li; Tim Dunn; Pavan Chandra Konda; Roarke Horstmeyer

doi:10.1364/ISA.2021.IW4A.4

OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
OSA Technical Digest (Optica Publishing Group, 2021),
paper IW4A.4
•https://doi.org/10.1364/ISA.2021.IW4A.4

Increasing a Microscope’s Effective Field of View via Overlapped Imaging and Machine Learning

Xing Yao, Haoran Xi, Kevin C. Zhou, Amey Chaware, Colin Cooke, Yuting Li, Tim Dunn, Pavan Chandra Konda, and Roarke Horstmeyer

Imaging Systems and Applications 2021

Washington, DC United States
19–23 July 2021
ISBN: 978-1-943580-89-7

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Machine Learning and Imaging I (IW4A)

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X. Yao, H. Xi, K. C. Zhou, A. Chaware, C. Cooke, Y. Li, T. Dunn, P. C. Konda, and R. Horstmeyer, "Increasing a Microscope’s Effective Field of View via Overlapped Imaging and Machine Learning," in OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), H. Hua, B. Javidi, M. Martinez-Corral, O. Matoba, A. Stern, S. Thibault, T. Alieva, J. Ke, F. Willomitzer, F. Okten, P. Silveira, P. Banerjee, E. Stoykova, D. Chu, J. Park, F. Imai, C. Joo, M. Digman, D. Gardner, S. Gladysz, D. LeMaster, S. Basu, and O. Korotkova, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper IW4A.4.

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Abstract

We demonstrate a multi-lenses microscopic imaging system that records over- lapping fields-of-view for high-efficiency automated specimen analysis. We show both in simulation and experiment how our system can achieve accurate target object detection on overlapped images.

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