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Catheter pose-dependent virtual angioscopy images for endovascular aortic repair: validation with a video graphics array (VGA) camera

Verónica García-Vázquez*, Florian Matysiak, Sonja Jäckle, Tim Eixmann, Malte Maria Sieren, Felix Von Haxthausen, Floris Ernst

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

Previous research reported catheter pose-dependent virtual angioscopy images for endovascular aortic repair (EVAR) (phantom studies) without any validation with video images. The goal of our study focused on conducting this validation using a video graphics array (VGA) camera. The spatial relationship between the coordinate system of the virtual camera and the VGA camera was computed with a Hand-Eye calibration so that both cameras produced similar images. A re-projection error of 3.18 pixels for the virtual camera and 2.14 pixels for the VGA camera was obtained with a designed three-dimensional (3D) printed chessboard. Similar images of the vessel (3D printed aorta) were acquired with both cameras except for the different depth. Virtual angioscopy images provide information from inside the vessel that may facilitate the understanding of the tip position of the endovascular tools while performing EVAR.

OriginalspracheEnglisch
Aufsatznummer20200010
ZeitschriftCurrent Directions in Biomedical Engineering
Jahrgang6
Ausgabenummer1
ISSN2364-5504
DOIs
PublikationsstatusVeröffentlicht - 17.09.2020

Fördermittel

Research funding: This study was supported by the German Federal Ministry of Education and Research (BMBF, Nav EVAR project, number 13GW0228) and the Ministry of Economic Affairs, Employment, Transport and Technology of Schleswig-Holstein.

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen
  2. SDG 9 – Industrie, Innovation und Infrastruktur
    SDG 9 – Industrie, Innovation und Infrastruktur

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