Paper
9 January 2025 3D reconstruction model of atlantoaxial joint gap based on Cxy-Net
Ruifang Zhou, Hongbo Zhao
Author Affiliations +
Proceedings Volume 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024); 1348607 (2025) https://doi.org/10.1117/12.3055745
Event: Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 2024, Chengdu, China
Abstract
One of the surgical devices used to treat cervical spine disorders. The atlantoaxial lateral block is fusion device. Atlantoaxial joint space reconstruction is one of the key steps in the use of the atlantoaxial lateral block fusion device, whereas the conventional 3D atlantoaxial joint space reconstruction suffered from low reconstruction precision and accuracy, as well as the inability to take into account its dynamic properties accurately. To address these issues, this work proposes a parallel segmentation reconstruction model. By using the patient's cervical spine CT datas as input, the atlantoaxial joint gap is reconstructed in 3D by the gap edge detection module and 3D reconstruction module of the model in this paper, and the visualized 3D model is output. In the gap edge detection module, an advanced image segmentation algorithm based on Cxy-Net is adopted to optimize and extract the details of the gap. The average Hausdorff distance (Hd) of this model is 10.5211 mm, the average symmetric surface distance (ASD) is 0.3861 mm, the average surface overlap (So) reaches 90.09%, the average Dice similary coefficient (Dice) is 0.8834, and the average accuracy (AC) is 0.8914. Compared with the conventional modeling, the model of the present paper improves the accuracy, Dice similary coefficient, and accuracy by about 15.37%, 8.96%, and 4.84% respectively.
(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Ruifang Zhou and Hongbo Zhao "3D reconstruction model of atlantoaxial joint gap based on Cxy-Net", Proc. SPIE 13486, Fourth International Conference on Computer Vision, Application, and Algorithm (CVAA 2024), 1348607 (9 January 2025); https://doi.org/10.1117/12.3055745
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
3D modeling

Data modeling

Computed tomography

Reconstruction algorithms

Performance modeling

Image segmentation

3D image reconstruction

Back to Top