XMARCUS: A Pathway Towards Remote Robotic Surgery Training}, is a compilation work of human-robot, human-artificial intelligence, and human-computer interaction.
The thesis provides a technical overview of the history of robotic surgery, present innovation, and future impacts. We present a behaviorist overview and describe our view of the overall direction of robotic surgery to enhance surgical training. We also discuss application towards future directions of translational medicine, adoption of surgical tools, and innovation within medicine. XMARCUS indicates the possibility of another artificial intelligence winter within surgery domain and presents a direction towards surgical training. Our macroscopic perspective and development of demo applications on third-party consoles demonstrates how to enhance robotic surgery training, provide future directions of minimally invasive surgery, and further enhance medical education. We also present the argument for a definitive direction of applications of artificial intelligence, the breakdown of its very definition, along with its proper application, in order to connect both the surgical and software communities for further steps in translational medicine. XMARCUS is not only a pathway towards applicable accessibility for surgical training, but also is a framework to allow further innovation in translational medicine for robotic surgery.
The thesis consists of 14 chapters divided into 3 parts. Part 1 provides a technical history background focused on the history of robotic surgery, the present hardware breakdown, applications and advancement of artificial intelligence and computer vision practices within the field. Part 2 highlights the disconnect between both surgical and software communities, and a pathway to integrating both fields towards translational medicine, specifically focusing on artificial intelligent practices by integrating machine learning for computer vision in the endoscopic space. Part 3 presents future research directions and important research questions to address, highlighting the future of surgery with the lack of physician accessibility to implementing artificial intelligence practices, focuses on providing an integration of remote robotic surgery training. / Master of Science / XMARCUS: A Pathway Towards Remote Robotic Surgery Training} is an avocation, proof of concept, and general overview of robotic surgery, its present predicament, and future impact of software engineering. There is an ever pressing need to integrate artificial intelligence practices within robotic surgery and minimally invasive surgery procedures. However, computing has faced a number of artificial intelligence winters with no viable means of application. Due to the lack of available data and machine learning models trained on such data, there is another permanence of an artificial intelligence winter, especially surgical applications. We also present the XMARCUS dataset, with over 12,000 images and a walk-through for crowdsource annotation process using Intel's OpenVino framework, where there has been less viable data. The focus is on the general overview of artificial intelligence, within the domain of machine learning for computer vision practices. This includes a discussion of virtual coaching and remote surgical training, specifically methods to further develop robotic surgery simulation software, in order to advance not solely the endoscopic space, but also the surgical training. Human-computer interaction models and theories, such as the Diffusion of Innovation, showcase the adaptation and timing of certain technologies, for viable application. We also present another concept focusing on the timing of technology to be introduced to help with translational medicine. Finally, we show an application in a series of proof concepts of remote virtual coaching for remote robotic surgical training including the psychomotor skills and FDA policy overview for implementing novel software practices to advance robotic surgery. With consideration towards remote surgery training and the universal push for creating credentialing and guidelines in robotic surgery, we discuss further disparities to showcase an ethical framework to enhance surgical training and implement novel software engineering practices.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/110894 |
| Date | 22 June 2022 |
| Creators | Nelson, Gunnar Beck |
| Contributors | Computer Science, Gracanin, Denis, Abbott, Amos L., Kafura, Dennis G. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | Creative Commons Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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