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Mobile and Low-cost Hardware Integration in Neurosurgical Image-Guidance


Mobile and Low-cost Hardware Integration in Neurosurgical Image-Guidance

Léger, Étienne (2021) Mobile and Low-cost Hardware Integration in Neurosurgical Image-Guidance. PhD thesis, Concordia University.

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It is estimated that 13.8 million patients per year require neurosurgical interventions worldwide, be it for a cerebrovascular disease, stroke, tumour resection, or epilepsy treatment, among others. These procedures involve navigating through and around complex anatomy in an organ where damage to eloquent healthy tissue must be minimized. Neurosurgery thus has very specific constraints compared to most other domains of surgical care. These constraints have made neurosurgery particularly suitable for integrating new technologies. Any new method that has the potential to improve surgical outcomes is worth pursuing, as it has the potential to not only save and prolong lives of patients, but also increase the quality of life post-treatment. In this thesis, novel neurosurgical image-guidance methods are developed, making use of currently available, low-cost off-the-shelf components. In particular, a mobile device (e.g. smartphone or tablet) is integrated into a neuronavigation framework to explore new augmented reality visualization paradigms and novel intuitive interaction methods. The developed tools aim at improving image-guidance using augmented reality to improve intuitiveness and ease of use. Further, we use gestures on the mobile device to increase interactivity with the neuronavigation system in order to provide solutions to the problem of accuracy loss or brain shift that occurs during surgery. Lastly, we explore the effectiveness and accuracy of low-cost hardware components (i.e. tracking systems and ultrasound) that could be used to replace the current high cost hardware that are integrated into commercial image-guided neurosurgery systems. The results of our work show the feasibility of using mobile devices to improve neurosurgical processes. Augmented reality enables surgeons to focus on the surgical field while getting intuitive guidance information. Mobile devices also allow for easy interaction with the neuronavigation system thus enabling surgeons to directly interact with systems in the operating room to improve accuracy and streamline procedures. Lastly, our results show that low-cost components can be integrated into a neurosurgical guidance system at a fraction of the cost, while having a negligible impact on accuracy. The developed methods have the potential to improve surgical workflows, as well as democratize access to higher quality care worldwide.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (PhD)
Authors:Léger, Étienne
Institution:Concordia University
Degree Name:Ph. D.
Program:Computer Science
Date:9 July 2021
Thesis Supervisor(s):Kersten-Oertel, Marta and Popa, Tiberiu
ID Code:988949
Deposited By: Ã�tienne Léger
Deposited On:29 Nov 2021 16:57
Last Modified:29 Nov 2021 16:57
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