ArticleJournal of biomedical optics2023
ArthroNavi framework: stereo endoscope-guided instrument localization for arthroscopic minimally invasive surgeries.
Article in Journal of biomedical optics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Advanced systems for intraoperative cartilage evaluation and treatment demonstrate early feasibility and a shift towards integrating artificial intelligence: A scoping review.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Article
- An EM-Tracked Approach for Calibrating the 3D Pose of Flexible Endoscopes.Annals of biomedical engineering · 2024Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Significance: As an example of a minimally invasive arthroscopic surgical procedure, arthroscopic osteochondral autograft transplantation (OAT) is a common option for repairing focal cartilage defects in the knee joints. Arthroscopic OAT offers considerable benefits to patients, such as less post-operative pain and shorter hospital stays. However, performing OAT arthroscopically is an extremely demanding task because the osteochondral graft harvester must remain perpendicular to the cartilage surface to avoid differences in angulation. Aim: We present a practical ArthroNavi framework for instrument pose localization by combining a self-developed stereo endoscopy with electromagnetic computation, which equips surgeons with surgical navigation assistance that eases the operational constraints of arthroscopic OAT surgery. Approach: A prototype of a stereo endoscope specifically fit for a texture-less scene is introduced extensively. Then, the proposed framework employs the semi-global matching algorithm integrating the matching cubes method for real-time processing of the 3D point cloud. To address issues regarding initialization and occlusion, a displaying method based on patient tracking coordinates is proposed for intra-operative robust navigation. A geometrical constraint method that utilizes the 3D point cloud is used to compute a pose for the instrument. Finally, a hemisphere tabulation method is presented for pose accuracy evaluation. Results: Experimental results show that our endoscope achieves 3D shape measurement with an accuracy of Conclusions: The effectiveness of the proposed ArthroNavi has been validated on a phantom femur. The potential contribution of this framework may provide a new computer-aided option for arthroscopic OAT surgery.
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