Modeling tissue temperature dynamics during laser exposure

  • Authors:
  • Loris Fichera;Diego Pardo;Leonardo S. Mattos

  • Affiliations:
  • Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy;Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy;Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genova, Italy

  • Venue:
  • IWANN'13 Proceedings of the 12th international conference on Artificial Neural Networks: advences in computational intelligence - Volume Part II
  • Year:
  • 2013

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Abstract

This paper presents the simulation and learning of soft tissue temperature dynamics when exposed to laser radiation. Monte Carlo simulation is used to represent the photon distribution in the tissue while machine learning techniques are used to obtain the mapping from controllable laser inputs (power, pulse rate and exposure time) to the correspondent changes in temperature. This model is required to predict the effects of laser-tissue interaction during surgery, i.e., tissue incision depth and carbonization.