Title
Control of Multi-Degree-of-Freedom Catheters in Unknown Environments: Exploring the Potential of Deep Learning and Augmented Reality
Author
Wu, D. (TU Delft Medical Instruments & Bio-Inspired Technology)
Contributor
Dankelman, J. (promotor) 
Vander Poorten, Emmanuel B. (promotor)
Degree granting institution
Delft University of Technology
Katholieke Universiteit Leuven
Date
2023-12-13
Abstract
Cardiovascular disease is currently one of the biggest threats to health. Specific types of cardiovascular disease include, but are not limited to, coronary artery disease, cardiac valve disorders, or peripheral arterial disease. The current gold standard for managing these conditions incorporates the use of catheters and guidewires for intravascular navigation. Following their insertion into the vascular system, these instruments facilitate a variety of procedures, such as stent placement, recanalization of vessel blockage, and radiofrequency ablation. Compared to more invasive open heart surgery, catheterization represents a minimally invasive approach. This offers several benefits, including smaller incisions, faster postoperative recovery, and improved aesthetic outcomes...
Subject
robotic catheter
deep learning
control, sensing
augmented reality
To reference this document use:
https://doi.org/10.4233/uuid:21af38b1-ae31-4247-adf2-dcbff8b9ebb1
ISBN
978-94-6384-521-2
Embargo date
2024-05-11
Part of collection
Institutional Repository
Document type
doctoral thesis
Rights
© 2023 D. Wu