Lensless Near-Field Imaging with Enhanced Deep Super-Resolution Towards Real-Time Intraoperative Tumor Classification

J. W. Czarske; J. W. Czarske; T. Wang; J. Wu; J. Wu; O. Uckermann; O. Uckermann; R. Galli; R. Kuschmierz; R. Kuschmierz

doi:10.1364/ISA.2022.ITu5E.1

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP)
Technical Digest Series (Optica Publishing Group, 2022),
paper ITu5E.1
•https://doi.org/10.1364/ISA.2022.ITu5E.1

Lensless Near-Field Imaging with Enhanced Deep Super-Resolution Towards Real-Time Intraoperative Tumor Classification

J. W. Czarske, T. Wang, J. Wu, O. Uckermann, R. Galli, and R. Kuschmierz

Imaging Systems and Applications 2022

Vancouver, British Columbia Canada
11–15 July 2022
ISBN: 978-1-957171-09-8

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Deep Learning, Computational Optics, Image Processing and Classification I (ITu5E)

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J. W. Czarske, T. Wang, J. Wu, O. Uckermann, R. Galli, and R. Kuschmierz, "Lensless Near-Field Imaging with Enhanced Deep Super-Resolution Towards Real-Time Intraoperative Tumor Classification," in Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP), Technical Digest Series (Optica Publishing Group, 2022), paper ITu5E.1.

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Abstract

A deep learning assisted fiber endoscopy is proposed. Resolutions beyond physical limitations are achieved, resulting in increased tumor diagnostic accuracy. This method is promising for rapid minimal-invasive intraoperative diagnosis.

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