Presentation + Paper
2 March 2022 Near real-time nerve visualization using coherent Raman scattering rigid endoscope and deep learning-based image processing for nerve-sparing surgery
Author Affiliations +
Abstract
In surgery, peripheral nerves should be preserved as much as possible to suppress the dysfunction and improve the quality of life after surgery. However, it is difficult to distinguish colorless, transparent, and thin nerves from other tissues. We had developed a coherent anti-Stokes Raman scattering (CARS) rigid endoscope to visualize nerves in a label-free manner. CARS allows for imaging without staining based on the information of molecular vibrations. In the conference, we show near real-time nerve visualization using CARS endoscopy and deep learning. We demonstrate that the image taken at 1.6 s/image satisfies the segmentation quality required for medical images.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Naoki Yamato, Hirohiko Niioka, Jun Miyake, and Mamoru Hashimoto "Near real-time nerve visualization using coherent Raman scattering rigid endoscope and deep learning-based image processing for nerve-sparing surgery", Proc. SPIE 11957, Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry, 119570B (2 March 2022); https://doi.org/10.1117/12.2609483
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KEYWORDS
Image segmentation

Denoising

Nerve

Raman scattering

Coherence imaging

Image processing

Endoscopy

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