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Biomedical subjects

Steven Dawson

Publications and source records attributed to Steven Dawson.

5 recordsLinked to original sources
PubMed2006

Procedural simulation: a primer.

Procedural simulation will be a revolutionary change in how health care providers maintain their proficiency and skill. Visionary leaders are already examining how this educational technique will be integrated into traditional curricula, and interventional specialties will be at the leading edge of this revolution. The role must be defined that simulation will play, new educational models must be developed around it, and studies must be performed that will meet the demands of a skeptical profession. Only then will the first truly revolutionary change in medical learning have been achieved since the advent of animal experimentation nearly 1,000 years ago.

Animals↗
PubMed2005

New approaches to computer-based interventional neuroradiology training.

For over 20 years, interventional methods have substantially improved the outcomes of patients with cardiovascular disease. However, these procedures require an intricate combination of visual and tactile feedback and extensive training periods. In this paper, a prototype of endovascular therapy training system is presented. A set of core simulation components applicable to most vascular procedures has been designed and integrated into a real-time high-fidelity interventional neuroradiology training system for the prompt treatment of ischemic stroke. We believe it will improve the quality of training and the speed of learning without putting patients at risk.

Computer Simulation↗
PubMed2003

Real-time PC based X-ray simulation for interventional radiology training.

The ability to simulate realistic fluoroscopic images in real-time is a key aspect of any interventional radiology training system. In this paper, we propose a method for rendering X-ray images in real-time on a PC with consumer level graphics hardware, while improving the quality of the images. Although volume rendering techniques form the basis of our algorithm, we studied the characteristics of actual X-ray images to develop a method that can provide a new level of realism. In addition, the integration of the various levels of information contained in a CT scan in the rendering pipeline can be exploited to produce even more realistic, patient-specific X-ray or fluoroscopic images. Although the results presented here are preliminary, the performance of multi-texturing and multi-stage rasterization features available on recent low-cost graphics hardware already allows us to render X-ray images at about 30 frames per second.

Algorithms↗