On the estimation of optoacoustic waves in retinal laser therapy using Gaussian processes

Abstract

This paper studies potentials of machine learning in terms of Gaussian processes (GPs) to learn optoacoustic waves generated in eye globe during retina laser therapy. This can be utilized to improve temperature measurements for feedback control and to understand tissue properties of the irradiated sites. The treatment of each site is performed in two phases: The first one is used for GP learning based on measurements from a transducer and its dynamical model, then, the learned GP is employed for estimating the waves during the second phase where the treatment is activated. The results demonstrate the effectiveness of the approach.