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BY 4.0 license Open Access Published by De Gruyter September 18, 2019

Catheter pose-dependent virtual angioscopy images visualized on augmented reality glasses

  • Felix von Haxthausen EMAIL logo , Sonja Jäckle , Jan Strehlow , Floris Ernst and Verónica García-Vázquez


Fluoroscopy and digital subtraction angiography provide guidance in endovascular aortic repair (EVAR) but introduce radiation exposure and require the administration of contrast agent. To overcome these disadvantages, previous studies proposed to display the pose of an electromagnetically (EM) tracked catheter tip within a three-dimensional virtual aorta on augmented reality (AR) glasses. For further guidance, we propose to create virtual angioscopy images based on the catheter tip pose within the aorta and to display them on HoloLens. The aorta was segmented from the computed tomography (CT) data using MeVisLab software. A landmarkbased registration allowed the calculation of the pose of the EM sensor in the CT coordinate system. The sensor pose was sent to MeVisLab running on a computer and a virtual angioscopy image was created at runtime based on the segmented aorta. When requested by HoloLens, the last encoded image was sent from MeVisLab to the AR glasses via Wi-Fi using a remote procedure call (gRPC), and then decoded and displayed on HoloLens. For evaluation purposes, the latency of transmitting and displaying the images was measured using two different lossy compression formats (namely JPEG and DXT1). A mean latency of 82 ms was measured for the JPEG format. On the other hand, using the DXT1 format, the mean latency was reduced by 87 %. This study proved the feasibility of creating pose-dependent virtual angioscopy images and displaying them on HoloLens. Additionally, the results showed that the DXT1 format outperformed the JPEG format regarding latency. The virtual angioscopy may add valuable additional information for guidance in radiation-sparing EVAR procedure approaches.

Published Online: 2019-09-18
Published in Print: 2019-09-01

© 2019 by Walter de Gruyter Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 Public License.

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