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Probabilistic Model for Laser Damage to the Human Retina
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH GRADUATE SCHOOL OF ENGINEERING AND MANAGEMENT
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Understanding how lasers interact with media during propagation is a premiere field of physics. The subject area known as laser bioeffects explores laser interactions with biological cells, tissues, organs, and bodies. This research includes laser applications used in medicine, establishes safe exposure limits for industry and academia, and generally studies the many effects of laser light on living creatures. The bioeffects community relies heavily on deterministic modeling and simulation tools to support experimental research into damage thresholds and laser effects. However, recent laser applications require a probabilistic approach to support risk management and analyses methodologies. Some probabilistic models exist, but their assumptions are largely biased due to sampling and reporting techniques. This research focuses on building the first-ever population-based probabilistic model for retinal damage using a statistical model of the optical properties and dimensions of the human eye. Simulated population distributions are used as input to propagation and thermal damage models for analysis. The results of this research are intended to provide a foundation for future probabilistic models and applications. The format of this document is two separate papers. The first is the development of the statistical eye model based on human covariance data An Analysis of the Influences of Biological Variance, Measurement Error, and Uncertainty on Retinal Photothermal Damage Threshold Studies. The paper examines trends in wavelength and time dependencies of damage thresholds. The second paper, Biological Variance-Based Dose Response Model for 514 to 1064 Nanometer Laser Exposures, is the application of the statistical eye model in the creation of the dose-response model. The model can be used to establish the design space in the development of future laser systems. It provides the foundation for a true population-based risk analysis tool for safety standards development.
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