Two-step curve fitting combined with a two-layered tissue model to quantify intrinsic fluorescence of cervical mucosal tissue in vivo
Journal
Proceedings of SPIE - The International Society for Optical Engineering
Journal Volume
11925
Date Issued
2021
Author(s)
Abstract
Fluorescence spectroscopy (FS) has been used to characterize tissue fluorophores in vivo for the diagnosis of precancers in the uterine cervix. In this study, a two-step curve fitting process is established to extract the intrinsic fluorescence intensity and spectrum of fluorophores including NADH and FAD in the epithelium and collagen crosslinks in the stroma. Forward Monte Carlo (MC) models of diffuse reflectance spectroscopy (DRS) and FS are replaced by artificial neuron networks to improve the computation speed. First, absorption and scattering coefficients of the two tissue layers and the epithelial thickness are estimated from DRS data. Second, the genetic algorithm is used to find the best set of intrinsic fluorescence parameters of the three fluorophores that best fit measured FS data. Results suggest that the two-layered tissue model outperforms conventional homogeneous tissue models in extracted tissue optical properties. Intrinsic fluorescence parameters are extracted from in-vivo spectra measured on 31 subjects. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Subjects
Artificial neuron network; Diffuse reflection spectroscopy; Fluorescence spectroscopy; Genetic algorithm; Monte Carlo method
SDGs
Other Subjects
Curve fitting; Fluorescence spectroscopy; Fluorophores; Genetic algorithms; Neural networks; Optical properties; Tissue; Artificial neuron networks; Curves fittings; Diffuse reflectance spectroscopy; Diffuse reflection spectroscopy; In-vivo; Intrinsic fluorescence; Layered tissue; MonteCarlo methods; Spectroscopy data; Tissue models; Monte Carlo methods
Type
conference paper