Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning

YoungJu Jo; YoungJu Jo; YoungJu Jo; YoungJu Jo; YoungJu Jo; Hyungjoo Cho; Hyungjoo Cho; Wei Sun Park; Wei Sun Park; Wei Sun Park; Geon Kim; Geon Kim; DongHun Ryu; DongHun Ryu; Young Seo Kim; Young Seo Kim; Young Seo Kim; Moosung Lee; Moosung Lee; Sangwoo Park; Mahn Jae Lee; Mahn Jae Lee; Hosung Joo; HangHun Jo; Seongsoo Lee; Sumin Lee; Hyun-seok Min; Hyun-seok Min; Won Do Heo; Won Do Heo; Won Do Heo; YongKeun Park; YongKeun Park; YongKeun Park; YongKeun Park

doi:10.1364/CLEO_AT.2022.ATh2I.6

Conference on Lasers and Electro-Optics
Technical Digest Series (Optica Publishing Group, 2022),
paper ATh2I.6
•https://doi.org/10.1364/CLEO_AT.2022.ATh2I.6

Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning

YoungJu Jo, Hyungjoo Cho, Wei Sun Park, Geon Kim, DongHun Ryu, Young Seo Kim, Moosung Lee, Sangwoo Park, Mahn Jae Lee, Hosung Joo, HangHun Jo, Seongsoo Lee, Sumin Lee, Hyun-seok Min, Won Do Heo, and YongKeun Park

CLEO: Applications and Technology 2022

San Jose, California United States
15–20 May 2022
ISBN: 978-1-957171-05-0

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Deep Learning for Enhanced Contrast Imaging (ATh2I)

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Y. Jo, H. Cho, W. S. Park, G. Kim, D. Ryu, Y. S. Kim, M. Lee, S. Park, M. J. Lee, H. Joo, H. Jo, S. Lee, S. Lee, H. Min, W. D. Heo, and Y. Park, "Label-free multiplexed microtomography of endogenous subcellular dynamics using generalizable deep learning," in Conference on Lasers and Electro-Optics, Technical Digest Series (Optica Publishing Group, 2022), paper ATh2I.6.

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Abstract

We report a deep-learning-based imaging technique to predict 3D multiplexed fluorescence signals based on label-free refractive index measurements. We demonstrate the retrieval of specific subcellular information without exogenous labeling or staining, enabling multiplexed molecular imaging across various spatiotemporal scales.

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