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Deep Learning to Refocus 3D Images

Yichen Wu, Yair Rivenson, Hongda Wang, Yilin Luo, Eyal Ben-David, Laurent A. Bentolila, Christian Pritz, and Aydogan Ozcan

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Abstract

High-throughput volumetric fluorescence microscopic imaging remains an important challenge in biology, life sciences and engineering. Imaging 3D fluorescent samples usually involves scanning to acquire images at different focal planes, reducing imaging speed and increasing potential photodamage to the sample. As an alternative approach, we have created a deep-learning-based framework, Deep-Z, to digitally refocus 2D fluorescence microscopic images onto user-defined 3D surfaces.

© 2020 Optical Society of America

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