Ultra-thin 3D lensless fiber endoscopy using diffractive optical elements and deep neural networks

被引:48
作者
Kuschmierz, Robert [1 ,2 ]
Scharf, Elias [2 ]
Ortegon-Gonzalez, David F. [1 ]
Glosemeyer, Tom [1 ]
Czarske, Juergen W. [1 ,2 ,3 ,4 ]
机构
[1] Tech Univ Dresden, Lab Measurement & Sensor Syst Tech, Helmholtzstr 18, D-01069 Dresden, Germany
[2] Tech Univ Dresden, Competence Ctr Biomed Computat Laser Syst BIOLAS, Dresden, Germany
[3] Tech Univ Dresden, Inst Appl Phys, Sch Sci, Dresden, Germany
[4] Tech Univ Dresden, Excellence Cluster Phys Life, Dresden, Germany
来源
LIGHT-ADVANCED MANUFACTURING | 2021年 / 2卷 / 04期
关键词
SELF-CALIBRATION; MULTIMODE; MICROSCOPY; LIGHT; SPEED; PROBE;
D O I
10.37188/lam.2021.030
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Minimally invasive endoscopes are indispensable in biomedicine. Coherent fiber bundles (CFBs) enable ultrathin lensless endoscopes. However, the propagation of light through a CFB suffers from phase distortions and aberrations that can cause images to be scrambled. The correction of such aberrations has been demonstrated using various techniques for wavefront control, especially using spatial light modulators (SLMs). This study investigates a novel aberration correction without SLM for the creation of an efficient and compact system. The memory effect of CFBs enables a paradigm shift in the use of static diffractive optical elements (DOEs) instead of dynamic modulation with SLM. We introduce DOEs produced by 2-photon polymerization lithography for phase conjugation on a CFB for focusing, raster scanning, and imaging. Furthermore, a DOE with random patterns is used to encode the three-dimensional (3D) object information in a 2D speckle pattern that propagates along the ultrathin CFB. Neural networks decode the speckles to retrieve the 3D object information using single-shot imaging. Both DOE methods have compact low-cost concepts in common, and both pave the way for minimally invasive 3D endomicroscopy with benefits for optical imaging in biomedicine.
引用
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页数:10
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