Parameter estimation and model reduction for retinal laser treatment
Manuel Schaller, Mitsuru Wilson, Viktoria Kleyman, Mario Mordm\"uller,, Ralf Brinkmann, Matthias A. M\"uller, Karl Worthmann

TL;DR
This paper develops a reduced-order model for retinal laser treatment that enables real-time model predictive control by efficiently approximating temperature distribution with parametric dependencies, and estimates key absorption parameters in pig eyes.
Contribution
It introduces a combined global-basis and empirical interpolation approach tailored for laser photocoagulation, improving computational efficiency and parameter estimation accuracy.
Findings
The proposed method outperforms Taylor-series approximation in computation time.
Sensitivity analysis shows higher impact of RPE absorption coefficient on temperature increase.
Case study successfully estimates absorption parameter ranges in porcine eyes.
Abstract
Laser photocoagulation is one of the most frequently used treatment approaches for retinal diseases such as diabetic retinopathy and macular edema. The use of model-based control, such as Model Predictive Control (MPC), enhances a safe and effective treatment by guaranteeing temperature bounds. In general, real-time requirements for model-based control designs are not met since the temperature distribution in the eye fundus is governed by a heat equation with a nonlinear parameter dependency. This issue is circumvented by representing the model by a lower-dimensional system which well-approximates the original model, including the parametric dependency. We combine a global-basis approach with the discrete empirical interpolation method, tailor its hyperparameters to laser photocoagulation, and show its superiority in comparison to a recently proposed method based on Taylor-series…
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Taxonomy
TopicsRetinal Diseases and Treatments · Retinal Development and Disorders · Glaucoma and retinal disorders
