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All-fiber Ultrafast Image Detection Enabled by Deep Learning by Zhoutian Liu; Lele Wang; Yuan Meng; Tiantian He; Sifeng He; Yousi Yang; Liuyue Wang; Jiading Tian; Dan Li; Ping Yan; Mali Gong; Qiang Liu; Qirong Xiao is a scholarly article available to read on EtoBox.

What is All-fiber Ultrafast Image Detection Enabled by Deep Learning about?

## Abstract Detection of dynamical scenes at ultrafast speeds serves as a foundation for modern engineering, chemistry, material science and biomedicine, et al. For biomedical applications, in vivo microscopic imaging is often required, which has led to the development of fiber-probe-based endoscopy. However, the combination of ultrafast image acquiring with fiber endoscopy has not yet been achieved, which is vital for exploration of transient biomedical phenomena. Here, we propose a scheme of all-fiber image detection at an ultrafast speed without any free-space optical elements. Image detection is achieved based on the transformation of two-dimensional spatial information into one-dimensional temporal pulsed signal streams by leveraging the high intermodal dispersion in a multimode fiber. Deep learning algorithms are subsequently deployed to reconstruct the images detected by the fiber probe from the temporal waveforms acquired at the other end of the fiber. The fiber probe can directly detect micron-scale objects without any bulk objective, and image detection has been experimentally realized with a high frame rate (15 Mfps), a large frame depth (104) and extremely short shutter

Author

Zhoutian Liu; Lele Wang; Yuan Meng; Tiantian He; Sifeng He; Yousi Yang; Liuyue Wang; Jiading Tian; Dan Li; Ping Yan; Mali Gong; Qiang Liu; Qirong Xiao

Publisher

Research Square Platform LLC

Published

2021

Language

EN