Zhu T, Jiang S, Yang Z, Zhou Z, Li Y, Ma S, Zhuo J. A neuroendoscopic navigation system based on dual-mode augmented reality for minimally invasive surgical treatment of hypertensive intracerebral hemorrhage.
Comput Biol Med 2022;
140:105091. [PMID:
34872012 DOI:
10.1016/j.compbiomed.2021.105091]
[Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/23/2021] [Accepted: 11/26/2021] [Indexed: 01/01/2023]
Abstract
BACKGROUND AND OBJECTIVE
Hypertensive intracerebral hemorrhage is characterized by a high rate of morbidity, mortality, disability and recurrence. Neuroendoscopy has been utilized for treatment as an advanced technology. However, traditional neuroendoscopy allows professionals to see only tissue surfaces, and the field of vision is limited, which cannot provide spatial guidance. In this study, an AR-based neuroendoscopic navigation system is proposed to assist surgeons in locating and clearing hematoma.
METHODS
The neuroendoscope can be registered through the vector closed loop algorithm. The single-shot method is designed to register medical images with patients precisely. Real-time AR is realized based on video stream fusion. Dual-mode AR navigation is proposed to provide comprehensive guidance from catheter implantation to hematoma removal. A series of experiments is designed to validate the accuracy and significance of this system.
RESULTS
The average root mean square error of the registration between medical images and patients is 0.784 mm, and the variance is 0.1426 mm. The pixel mismatching degrees are less than 1% in different AR modes. In catheter implantation experiments, the average error of distance is 1.28 mm, and the variance is 0.43 mm, while the average error of angles is 1.34°, and the variance is 0.45°. Comparative experiments are also conducted to evaluate the feasibility of this system.
CONCLUSION
This system can provide stereo images with depth information fused with patients to guide surgeons to locate targets and remove hematoma. It has been validated to have high accuracy and feasibility.
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