Cognitive Supervision for Robot-Assisted Minimally Invasive Laser Surgery

Biomedical Engineering, Robotics and Automation, User Interfaces and Human Computer Interaction, Minimally Invasive Surger

Identification of Tissue Optical Properties During Thermal Laser-Tissue Interactions: An Ensemble Kalman Filter-Based Approach

In this paper, we propose a computational framework to estimate the physical properties that govern the thermal response of laser-irradiated tissue. We focus in particular on two quantities, the absorption and scattering coefficients, which describe the optical absorption of light in the tissue and whose knowledge is vital to correctly plan medical laser treatments. To perform the estimation, we utilize an implementation of the Ensemble Kalman Filter (EnKF), a type of Bayesian filtering algorithm for data assimilation. Unlike prior approaches, in this work we estimate the tissue optical properties based on observations of the tissue thermal response to laser irradiation. This method has the potential for straightforward implementation in a clinical setup, as it would only require a simple thermal sensor, e.g., a miniaturized infrared camera. Because the optical properties of tissue can undergo shifts during laser exposure, we employ a variant of EnKF capable of tracking time-varying parameters. Through simulated experimental studies, we demonstrate the ability of the proposed technique to identify the tissue optical properties and track their dynamic changes during laser exposure, while simultaneously tracking changes in the tissue temperature at locations beneath the surface. We further demonstrate the framework's capability in estimating additional unknown tissue properties (i.e., the volumetric heat capacity and thermal conductivity) along with the optical properties of interest.Comment: 20 pages, 9 figure

learning the temperature dynamics during thermal laser ablation

Given the research problem outlined in the previous chapter, here we focus on the development of a methodology to learn the temperature dynamics of tissues subject to thermal laser ablation

realization of a cognitive supervisory system for laser microsurgery

Based on the models presented in Chaps. 4 and 5, here we describe the development of a prototypical supervisory system for laser microsurgery

Losing Focus: Can It Be Useful in Robotic Laser Surgery?

This paper proposes a method to regulate the tissue temperature during laser surgery by robotically controlling the laser focus. Laser-tissue interactions are generally considered hard to control due to the inherent inhomogeneity of biological tissue, which can create significant variability in its thermal response to laser irradiation. In this study, we use methods from nonlinear control theory to synthesize a temperature controller capable of working on virtually any tissue type without any prior knowledge of its physical properties. The performance of the controller is evaluated in ex-vivo experiments.Comment: Provisionally Accepted at the Hamlyn Symposium on Medical Robotics 202

background laser technology and applications to clinical surgery

The goal of this chapter is to provide the background that frames the research described in this dissertation. Principles and concepts relevant to the content of subsequent chapters are introduced here. Because this work resides at the intersection of laser-tissue interaction with computer-assisted surgery, the basics of laser technology are introduced here

Cognitive Supervision for Robot-Assisted Minimally Invasive Laser Surgery

Biomedical Engineering, Robotics and Automation, User Interfaces and Human Computer Interaction, Minimally Invasive Surger