Extracting isovolumes from three-dimensional torso geometry using PROLOG

DefibViz: a visualization tool for the assessment of electrode parameters on transthoracic defibrillation thresholds

DefibViz is a software application developed for defibrillation simulation and visualization. It exploits both surface techniques and methods for the interactive exploration of volumetric datasets for the analysis of transthoracic defibrillation simulation results. DefibViz\ has a graphical user interface for the specification of the shape, size, position, and applied voltage of a defibrillator's electrodes. An option is provided for using 3-D slice plane widgets, which operate on the volumetric datasets, such that the distribution of the voltage gradient induced by an electric shock can be visually inspected in various tissues throughout the myocardium and torso. One goal of DefibViz is to enhance understanding of how electrode parameters relate to the change of the voltage gradient distribution throughout the heart, which may help lead to optimal defibrillator design. DefibViz; is significant, in that, it is built by using an open-source graphics and visualization framework providing a platform for subsequent modifiability and extensibility. Moreover, it integrates simulation and visualization techniques, which previously required the running of several independent software executables, into an enhanced, seamless, and comprehensive software application.

A Prolog-based centroid algorithm for isovolume extraction from finite element torso simulations

Computer modeling and simulation of the human torso provides a rapid and non-invasive means to observe the effects of implanted defibrillators. The objective of this study was to improve a method of extracting data from an implanted defibrillator simulation for subsequent visualization. Electrical quantities, such as the potential and gradient fields, are computed at points throughout various regions of a three-dimensional (3-D) torso model via a finite element solution. Software is then implemented in the Prolog language to extract and visualize a subset of the data, from within any subregion of the model, satisfying a given declarative constraint. In past work, membership in these subsets had been determined solely by the electrical quantities at the vertices of the tetrahedral elements within the model along with an arbitrary choice made by the user. However, this study expands upon previous work to utilize an alternative means of classification, calculating the centroid of each tetrahedron and assigning electrical properties to these centroids based on the distances of each centroid to the four corners of the tetrahedron. After the modifications, it is expected that the extracted subsets of the model will represent the data in a more realistic and conservative manner and provide more insight into the process of defibrillation than previous methods of data extraction and visualization.