Guangdong University of Technology

Tao Huang

Huiyang Wang

Weina Zhang

Jianglei Di

Liyun Zhong

Yuheng Wang

Yuwen Qin

The present disclosure of some embodiments provide a phase reconstruction method for differential interference contrast microscopy based on a pix2pix network, the method comprising the following steps: S, constructing an end-to-end deep learning strategy based on the pix2pix network; S, collecting and constructing dataset; S, Training the pix2pix network; S, analyzing network accuracy and convergence, and recording error curves of the datasets; S, analyzing network performance based on error curves of the training set and the test set; S, performing quantitative phase reconstruction for differential interference contrast microscopy using the trained pix2pix network.

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Guangzhou, China

Tao Huang