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Proceedings Paper

Deep learning allows enhanced detection of surface plasmon scattering (Conference Presentation)
Author(s): Gwiyeong Moon; Taehwang Son; Hongki Lee; Donghyun Kim

Paper Abstract

We investigate a way to detect images of surface plasmon scattering using deep learning approach. Unlike fluorescence imaging, the image of surface plasmon scattering shows much worse resolution due to propagation length of surface plasmon polariton. In this work, deep learning approach is taken to address this issue and to discriminate multiple target objects under complex and noisy environment. Conventional detection method based on fourier filtering and deconvolution was employed to compare the performance of the proposed method. It was shown that deep learning improves the accuracy by about six times, and especially more useful in noisy environment.

Paper Details

Date Published: 10 March 2020
Proc. SPIE 11257, Plasmonics in Biology and Medicine XVII, 112570N (10 March 2020); doi: 10.1117/12.2544169
Show Author Affiliations
Gwiyeong Moon, Yonsei Univ. (Korea, Republic of)
Taehwang Son, Massachusetts General Hospital (United States)
Hongki Lee, Yonsei Univ. (Korea, Republic of)
Donghyun Kim, Yonsei Univ. (Korea, Republic of)

Published in SPIE Proceedings Vol. 11257:
Plasmonics in Biology and Medicine XVII
Tuan Vo-Dinh; Ho-Pui A. Ho; Krishanu Ray, Editor(s)

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