Open AccessPerformance of measurands in time-domain optical brain imaging: depth selectivity versus contrast-to-noise ratio
Author(s) -
Aleh Sudakou,
Ying-Hsi Lin,
Heidrun Wabnitz,
Stanisław Wojtkiewicz,
Adam Liebert
Publication year - 2020
Publication title -
biomedical optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.362
H-Index - 86
ISSN - 2156-7085
DOI - 10.1364/boe.397483
Subject(s) - detector , optics , contrast (vision) , monte carlo method , signal to noise ratio (imaging) , absorption (acoustics) , noise (video) , imaging phantom , photon , contrast to noise ratio , attenuation coefficient , physics , materials science , image quality , mathematics , statistics , computer science , artificial intelligence , image (mathematics)
Time-domain optical brain imaging techniques introduce a number of different measurands for analyzing absorption changes located deep in the tissue, complicated by superficial absorption changes and noise. We implement a method that allows analysis, quantitative comparison and performance ranking of measurands under various conditions - including different values of reduced scattering coefficient, thickness of the superficial layer, and source-detector separation. Liquid phantom measurements and Monte Carlo simulations were carried out in two-layered geometry to acquire distributions of times of flight of photons and to calculate the total photon count, mean time of flight, variance, photon counts in time windows and ratios of photon counts in different time windows. Quantitative comparison of performance was based on objective metrics: relative contrast, contrast-to-noise ratio (CNR) and depth selectivity. Moreover, the product of CNR and depth selectivity was used to rank the overall performance and to determine the optimal source-detector separation for each measurand. Variance ranks the highest under all considered conditions.