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Application of RESNET50 Convolution Neural Network for the Extraction of Optical Parameters in Scattering Media
April 26, 2024, 4:42 a.m. | Bowen Deng, Yihan Zhang, Andrew Parkes, Alex Bentley, Amanda Wright, Michael Pound, Michael Somekh
cs.LG updates on arXiv.org arxiv.org
Abstract: Estimation of the optical properties of scattering media such as tissue is important in diagnostics as well as in the development of techniques to image deeper. As light penetrates the sample scattering events occur that alter the propagation direction of the photons in a random manner leading degradation of image quality. The distribution of the scattered light does, however, give a measure of the optical properties such as the reduced scattering coefficient and the absorption …
abstract application arxiv convolution convolution neural network cs.lg development diagnostics events extraction image light media network neural network optical parameters physics.optics propagation resnet50 sample type
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