An augmented reality system characterization of placement accuracy in neurosurgery. (February 2020)

• Record Type: Journal Article
• Authors: Nguyen, Nhu Q.; Cardinell, Jillian; Ramjist, Joel M.; Lai, Philips; Dobashi, Yuta; Guha, Daipayan; Androutsos, Dimitrios; Yang, Victor X.D.
• Is Part Of: Journal of clinical neuroscience. Volume 72(2020)
• Page Start: 392
• Page End: 396
• Publication Date: 2020-02
• Subjects: Augmented reality -- Neurosurgical navigation -- Microsoft HoloLens -- Placement accuracy; Brain -- Surgery -- Periodicals; Neurosciences -- Periodicals; Nervous system -- Surgery -- Periodicals; Brain -- surgery -- Periodicals; Neurosurgical Procedures -- Periodicals; Neurosciences -- Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.jocn.2019.12.014
• Languages: English
• ISSNs: 0967-5868

Abstract

Abstract: Computer assisted navigation (CAN) is a technology which has been available for commercial use in operating rooms for quite some time now. CAN relies on the information presented in patient imaging (usually CT or MRI images) and the surgical site. The method for registration between these two sets of data is crucial for safe image guided navigation during surgery. Although the existing technologies are extremely accurate, they still pose problems in the operating. Motivation for this study is to explore the possibility of using augmented reality (AR) to improve ease of use for surgical navigation and provide a system which complements the existing operating room workflow. As with all commercially available surgical navigation systems, registration accuracy is of utmost important to maintain patient safety. In this paper, we propose a novel method to quantify registration accuracy for augmented reality (AR) devices in neurosurgery.