Prof. Katrin Ellermann Profile

Prof. Katrin Ellermann

at Technische Univ. Graz

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Proceedings Article | 16 March 2020 Paper

A comprehensive workflow and framework for immersive virtual endoscopy of dissected aortae from CTA data

Jan Egger, Simon Gunacker, Antonio Pepe, Gian Marco Melito, Christina Gsaxner, Jianning Li, Katrin Ellermann, Xiaojun Chen

Proceedings Volume 11315, 1131531 (2020) https://doi.org/10.1117/12.2559239

KEYWORDS: Virtual reality, Visualization, Blood, Aorta, Computed tomography, 3D modeling, Medicine, Endoscopy, Blood circulation, Medical research

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The human organism is a highly complex system that is prone to various diseases. Some diseases are more dangerous than others, especially those that affect the circulatory system or the aorta in particular. The aorta is the largest artery in the human body. Its wall comprises several layers. When the intima, i.e. the innermost layer of the aortic wall, tears, blood enters and propagates between the layers causing them to separate. This is known as aortic dissection (AD). Without immediate treatment, an AD may kill 33% of patients within the first 24 hours, 50% of patients within 48 hours, and 75% of patients within 2 weeks. However, proper treatment is still subject to research and active discussion. By providing a deeper understanding of aortic dissections, this work aims to contribute to the continuous improvement of AD diagnosis and treatment by presenting AD in a new, immersive visual experience: Virtual Reality (VR). The visualization is based on Computed Tomography (CT) scans of human patients suffering from an AD. Given a scan, relevant visual information is segmented, refined and put into a 3D scene. Further enhanced by blood flow simulation and VR user interaction, the visualization helps in better understanding AD. The current implementation serves as a prototype and is considered to be extended by minimizing user interaction when new CT scans are loaded into VR (i) and by providing an interface to feed the visualization with simulation data provided by mathematical models (ii).

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