Extracting autofluorescence spectral shape and intensity from uterine cervical mucosa using monte-carlo based two-layered tissue models

Mok C.-IKUNG-BIN SUNG2021-09-022021-09-022020https://www.scopus.com/inward/record.uri?eid=2-s2.0-85091395785&partnerID=40&md5=49084de8b9dd355e7eb89880f6c42388https://scholars.lib.ntu.edu.tw/handle/123456789/581531Two-layered diffuse reflectance and fluorescence Monte Carlo (MC) models are developed to extract layer-specific intrinsic fluorescence spectra and intensity of in-vivo cervical mucosa. Artificial neural networks replace MC simulations to efficiently solve the inverse problem. ? OSA 2020 ? 2020 The Author(s)Fluorescence; Monte Carlo methods; Photonics; Autofluorescence; Diffuse reflectance; In-vivo; Intrinsic fluorescence; Layered tissue; MC simulation; Spectral shapes; Inverse problemsExtracting autofluorescence spectral shape and intensity from uterine cervical mucosa using monte-carlo based two-layered tissue modelsconference paper2-s2.0-85091395785