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Proceedings Paper

Fast optical coherence tomography image enhancement using deep learning for smart laser surgery: preliminary study in bone tissue
Author(s): Yakub A. Bayhaqi; Georg Rauter; Alexander Navarini; Philippe C. Cattin; Azhar Zam
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Paper Abstract

One of the most common image denoising technique used in Optical Coherence Tomography (OCT) is the frame averaging method. Inherent to this method is that the more images are used, the better the resulting image. This approach comes, however, at the price of increased acquisition time and introduced sensitivity to motion artifacts. To overcome these limitations, we proposed an artificial neural network architecture able to imitate an averaging method using only a single image frame. The reconstructed image has an improvement in the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) parameters compared to the original image. Additionally, we also observed an improvement in the sharpness of the denoised images. This result shows the possibility to use this method as a pre-processing step for real-time tissue classification in smart laser surgery especially in bone surgery.

Paper Details

Date Published: 3 October 2019
PDF: 6 pages
Proc. SPIE 11207, Fourth International Conference on Applications of Optics and Photonics, 112070Z (3 October 2019); doi: 10.1117/12.2527293
Show Author Affiliations
Yakub A. Bayhaqi, Univ. Basel (Switzerland)
Georg Rauter, Univ. Basel (Switzerland)
Alexander Navarini, Univ. Basel (Switzerland)
Philippe C. Cattin, Univ. Basel (Switzerland)
Azhar Zam, Univ. Basel (Switzerland)

Published in SPIE Proceedings Vol. 11207:
Fourth International Conference on Applications of Optics and Photonics
Manuel Filipe P. C. M. Martins Costa, Editor(s)

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