A deep learning-based hybrid approach for the solution of multiphysics problems in electrosurgery.

Multiphysics modeling of evolving topology in the electrosurgical dissection of soft hydrated tissues is a challenging problem, requiring heavy computational resources. In this paper, we propose a hybrid approach that leverages the regressive capabilities of deep convolutional neural networks (CNN) with the precision of conventional solvers to accelerate Multiphysics computations. The electro-thermal problem is solved using a finite element method (FEM) with a Krylov subspace-based iterative solver and a deflation-based block preconditioner.

A Multiphysics Model for Radiofrequency Activation of Soft Hydrated Tissues.

A multi-physics model has been developed to investigate the effects of cellular level mechanisms on the electro-thermo-mechanical response of hydrated soft tissues with radiofrequency (RF) activation. A micromechanical model generates an equation of state (EOS) that provides the additional pressure arising from evaporation of intra- and extracellular water as well as temperature to the continuum level thermo-mechanical model. A level set method is used to capture the interfacial evolution of tissue damage with the level set evolution equation derived from the second law of thermodynamics, which is consistent with Griffith's fracture evolution criterion.

FUSE certification enhances performance on a virtual computer based simulator for dispersive electrode placement.

Background: The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) has developed the fundamental use of surgical energy (FUSE) didactic curriculum in order to further understanding of the safe use of surgical energy. The virtual electrosurgical skill trainer (VEST) is being developed as a complementary simulation-based curriculum, with several modules already existing. Subsequently, a new VEST module has been developed about dispersive electrode placement.

A physics-based algorithm for real-time simulation of electrosurgery procedures in minimally invasive surgery.

Background: High-frequency electricity is used in the majority of surgical interventions. However, modern computer-based training and simulation systems rely on physically unrealistic models that fail to capture the interplay of the electrical, mechanical and thermal properties of biological tissue.

Methods: We present a real-time and physically realistic simulation of electrosurgery by modelling the electrical, thermal and mechanical properties as three iteratively solved finite element models.