title: Non-invasive determination of the absorption coefficient of the brain from time-resolved reflectance using a neural network.
abstract: We investigated the performance of a neural network for derivation of the absorption coefficient of the brain from simulated non-invasive time-resolved reflectance measurements on the head. A five-layered geometry was considered assuming that the optical properties (except the absorption coefficient of the brain) and the thickness of all layers were known with an uncertainty. A solution of the layered diffusion equation was used to train the neural network. We determined the absorption coefficient of the brain with an RMS error of <6% from reflectance data at a single distance calculated by diffusion theory. By applying the neural network to reflectance curves obtained from Monte Carlo simulations, similar errors were found.
authors.affiliation: Institut für Lasertechnologien in der Medizin und Meßtechnik, Helmholtzstraße 12, 89081 Ulm, Germany.
authors.forename: Marion
authors.initials: M
authors.lastname: Jäger
authors.forename: Alwin
authors.initials: A
authors.lastname: Kienle
mesh_terms: D000042:Absorption; D001921:Brain / Q000502:physiology; D006439:Hemodynamics; D006801:Humans; D009010:Monte Carlo Method; D016571:Neural Networks, Computer; D055620:Optical Phenomena; D013997:Time Factors