Human-Computer Interaction

Augmented Coronary Training


This project is already completed.

Background

Stenosis of the coronal arteries is a life threatening condition. Blood vessels narrow down and blood flow is limited and finally interrupted. Fortunately, angiography methods can help in many such cases once the stenosis is detected, localized, and quantified. Angiography uses low-dosage X-ray visualization. The x-ray emitter and collector are mounted at a so-called C-bow (C-Bogen) which can be freely positioned in physical 3D space around a patient. At the same time, the physician can control and operate minimal invasive instruments at the tip of very fine wires which they steer through the vessels to the point of interest based on the 2D images of the X-ray, which will show a camera perspective defined by the C-bows position and orientation. Hence, due to the many different 3D reference systems to cope with, mental 3D rotations is required by the operators, and operators have to have a very good understanding of the 3D anatomy of coronal arteries. To train these skills at the real angiography machines either with probs or with real patients is problematic since it does generate unnecessary radiation exposure.

Tasks

Design and development of an Augmented Reality (AR) teaching and training app for prospective cardiologists to teach the understanding of the 3D anatomy of the coronal arteries. The app should help to enable physicians to properly detect, localize, and quantify potential stenosis of the coronal arteries and to apply the adequate angiography method. The app should contain the anatomies of several patients by importing data from CT scans. It would be desirable, if the app would either mimic operation of a real angiography machine, e.g., Siemens Artis U oder Philips Allura or be placed at such a device as a prop. The used display system has to be found during the design. The design space include tablet-like displays as well as head-mounted AR displays like the new Hololens 2 or the magic leap.

Prerequisites

Cooperation

This project is in cooperation with the university’s INTUS clinic.

Cooperation Partners

Prof. Dr. W. Voelker
Universitätsklinikum, INTUS
Dr. Nils Petri
Universitätsklinikum

Contact Persons at the University Würzburg

Marc Erich Latoschik (Primary Contact Person)
Mensch-Computer-Interaktion, Universität Würzburg
marc.latoschik@uni-wuerzburg.de

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