Artificial neural network based method to estimate optical properties in biological tissues for noise reduction

Yusaku Takai; Yu Shimojo; Yu Shimojo; Takahiro Nishimura; Kunio Awazu; Kunio Awazu

doi:10.1364/TRANSLATIONAL.2022.JM3A.3

Biophotonics Congress: Biomedical Optics 2022 (Translational, Microscopy, OCT, OTS, BRAIN)
Technical Digest Series (Optica Publishing Group, 2022),
paper JM3A.3
•https://doi.org/10.1364/TRANSLATIONAL.2022.JM3A.3

Artificial neural network based method to estimate optical properties in biological tissues for noise reduction

Yusaku Takai, Yu Shimojo, Takahiro Nishimura, and Kunio Awazu

Microscopy Histopathology and Analytics 2022

Fort Lauderdale, Florida United States
24–27 April 2022
ISBN: 978-1-957171-03-6

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Joint Poster Session I On Site (JM3A)

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Y. Takai, Y. Shimojo, T. Nishimura, and K. Awazu, "Artificial neural network based method to estimate optical properties in biological tissues for noise reduction," in Biophotonics Congress: Biomedical Optics 2022 (Translational, Microscopy, OCT, OTS, BRAIN), Technical Digest Series (Optica Publishing Group, 2022), paper JM3A.3.

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Abstract

An artificial neural network was constructed to predict optical properties of biological tissues from measured spectral values with noise. Numerical calculation revealed the improvement of estimation accuracy of the optical properties from the noised values.

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