Version 1
: Received: 5 July 2023 / Approved: 5 July 2023 / Online: 5 July 2023 (08:32:01 CEST)
How to cite:
He, J.; Guo, Z.X.; Zeng, Y.X.; Su, X.Y.; Xian, P.G. Pre-planning of Individualized Talus Implants Based on Computed Tomography-Automated Segmentation. Preprints2023, 2023070273. https://doi.org/10.20944/preprints202307.0273.v1
He, J.; Guo, Z.X.; Zeng, Y.X.; Su, X.Y.; Xian, P.G. Pre-planning of Individualized Talus Implants Based on Computed Tomography-Automated Segmentation. Preprints 2023, 2023070273. https://doi.org/10.20944/preprints202307.0273.v1
He, J.; Guo, Z.X.; Zeng, Y.X.; Su, X.Y.; Xian, P.G. Pre-planning of Individualized Talus Implants Based on Computed Tomography-Automated Segmentation. Preprints2023, 2023070273. https://doi.org/10.20944/preprints202307.0273.v1
APA Style
He, J., Guo, Z.X., Zeng, Y.X., Su, X.Y., & Xian, P.G. (2023). Pre-planning of Individualized Talus Implants Based on Computed Tomography-Automated Segmentation. Preprints. https://doi.org/10.20944/preprints202307.0273.v1
Chicago/Turabian Style
He, J., Xiu yun Su and Pei guo Xian. 2023 "Pre-planning of Individualized Talus Implants Based on Computed Tomography-Automated Segmentation" Preprints. https://doi.org/10.20944/preprints202307.0273.v1
Abstract
Fractures of the talar neck and body are associated with spine fractures and scoliosis deformity, which affect cosmetic appearance and cause difficulty in ambulation. The implant design for talus surgery is thriving as a functional alternative in case of severe talar destruction, focusing on segmentation and reconstruction of the talus’s shape. However, manual segmentation of the talus is time-consuming and subjective. In this study we exploited the automatic segmentation framework to efficiently train a deep learning-based model to accurately segment the talus based on computed tomography imaging. We developed three model configurations with nnU-Net and investigated their Dice similarity coefficients (DSC) and 95% Hausdorff distances (HD95) for talus segmentation on a CT image dataset. The three configurations performed well (DSC > 0.95, HD95 < 0.6). When tested on the same samples, one of the configurations was more efficient while ensuring higher accuracy. We propose to focus on talus anatomic variations with increasing age based on this framework and apply it to clinical trials at the next stage.
Keywords
medical image segmentation; talus; deep learning; nnU-Net
Subject
Engineering, Bioengineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
