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Increasing a microscope’s effective field of view via overlapped imaging and machine learning

Publication ,  Journal Article
Yao, X; Xi, H; Zhou, KC; Chaware, A; Cooke, C; Li, Y; Dunn, T; Konda, PC; Horstmeyer, R
Published in: Optics InfoBase Conference Papers
January 1, 2021

We demonstrate a multi-lenses microscopic imaging system that records overlapping 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.

Duke Scholars

Published In

Optics InfoBase Conference Papers

EISSN

2162-2701

Publication Date

January 1, 2021
 

Citation

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Yao, X., Xi, H., Zhou, K. C., Chaware, A., Cooke, C., Li, Y., … Horstmeyer, R. (2021). Increasing a microscope’s effective field of view via overlapped imaging and machine learning. Optics InfoBase Conference Papers.
Yao, X., 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.” Optics InfoBase Conference Papers, January 1, 2021.
Yao X, Xi H, Zhou KC, Chaware A, Cooke C, Li Y, et al. Increasing a microscope’s effective field of view via overlapped imaging and machine learning. Optics InfoBase Conference Papers. 2021 Jan 1;
Yao, X., et al. “Increasing a microscope’s effective field of view via overlapped imaging and machine learning.” Optics InfoBase Conference Papers, Jan. 2021.
Yao X, Xi H, Zhou KC, Chaware A, Cooke C, Li Y, Dunn T, Konda PC, Horstmeyer R. Increasing a microscope’s effective field of view via overlapped imaging and machine learning. Optics InfoBase Conference Papers. 2021 Jan 1;

Published In

Optics InfoBase Conference Papers

EISSN

2162-2701

Publication Date

January 1, 2021