A COMPARISON OF PARTICLE FILTER ALGORITHMS APPLIED TO THE HYPERTHERMIA TREATMENT OF CANCER INDUCED BY NEAR-INFRARED LASER
BERNARD LAMIEN1; HELCIO RANGEL BARRETO ORLANDE1; GUILLERMO ENRIQUE ELIÇABE2
1 Federal University of Rio de Janeiro, PEM/COPPE; 2 Inst. Mat. Science and Technology (INTEMA), Univ. Mar del Plata (CONICET)
doi:10.20906/CPS/USM-2016-0031
Resumo
In this paper, the hyperthermia treatment of cancer induced by near-infrared laser light is formulated as a state estimation problem and solved with Particle Filters. Although the hyperthermia treatment of cancer has been addressed in the literature by different computational methods, these usually involved deterministic analyses. On the other hand, state space representation of the problem in the Bayesian framework allows for the analyses of uncertainties present in the mathematical formulation of the problem, as well as in the measured data of observable variables that might be eventually available. The physical problem considered in this paper involves the irradiation with a laser in the near infrared range, of a multi-layered medium composed of several tissues. The layer representing the tumor is assumed to be loaded with plasmonic nanoparticles in order to enhance the hyperthermia effects and to limit such effects to the tumor region. The laser tissue interaction is modelled as a coupled radiation-bioheat transfer problem. For the solution of the inverse problem, local temperature measurements are assumed available. The inverse problem of temperature field estimation together with the fluence rate distribution is solved with three different Particle Filters, namely: the SIR Filter (Sampling Importance Resampling Filter), the ASIR Filter (Auxiliary Sampling Importance Resampling Filter) and the LIU & WEST Filter; their performance are compared in terms of solution accuracy and computational time.
Palavras-chave: INVERSE PROBLEM,; PARTICLE FILTER; HYPERTHERMIA; NANOPARTICLES