Multispectral image reconstruction with neural networks for minimally invasive 3D lensless fiber endoscopy using a diffuser

Tom Glosemeyer; Yazhi Zheng; Julian Lich; Robert Kuschmierz; Jürgen Czarske

doi:10.1117/12.2621196

20 May 2022 Multispectral image reconstruction with neural networks for minimally invasive 3D lensless fiber endoscopy using a diffuser

Tom Glosemeyer, Yazhi Zheng, Julian Lich, Robert Kuschmierz, Jürgen Czarske

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Proceedings Volume PC12136, Unconventional Optical Imaging III; PC121360A (2022) https://doi.org/10.1117/12.2621196
Event: SPIE Photonics Europe, 2022, Strasbourg, France

Abstract

Endoscopy through coherent fiber bundles plays a significant role in industrial and medical imaging. By using a diffractive optical element in form of a diffuser on the distal side, the information of the measurement volume is encoded as 2D speckle patterns on the camera. This allows minimally invasive single-shot 3D imaging through a flexible low-cost endoscope with a diameter of less than 1 mm. Neural networks are employed to get fast image reconstructions from the speckle patterns with high quality. Moreover, multispectral speckle coding is used to increase the amount of transferred information and thus improving imaging capabilities.

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Tom Glosemeyer, Yazhi Zheng, Julian Lich, Robert Kuschmierz, and Jürgen Czarske "Multispectral image reconstruction with neural networks for minimally invasive 3D lensless fiber endoscopy using a diffuser", Proc. SPIE PC12136, Unconventional Optical Imaging III, PC121360A (20 May 2022); https://doi.org/10.1117/12.2621196

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KEYWORDS

Diffusers

Endoscopy

Neural networks

Image restoration

3D image processing

Multispectral imaging

3D metrology

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