Can computer vision / artificial intelligence locate key reference points and make clinically relevant measurements on axillary radiographs?

Matsen FA III, Gupta A (2014) Axillary view: arthritic glenohumeral anatomy and changes after ream and run. Clin Orthop Relat Res 472:894–902. https://doi.org/10.1007/s11999-013-3327-6

Article  PubMed  Google Scholar 

von Eisenhart-Rothe R, Müller-Gerbl M, Wiedemann E, Englmeier K-H, Graichen H (2008) Functional malcentering of the humeral head and asymmetric long-term stress on the glenoid: potential reasons for glenoid loosening in total shoulder arthroplasty. J Shoulder Elb Surg 17:695–702. https://doi.org/10.1016/j.jse.2008.02.008

Article  Google Scholar 

Geng EA, Cho BH, Valliani AA, Arvind V, Patel AV, Cho SK, Kim JS, Cagle PG (2022) Development of a machine learning algorithm to identify total and reverse shoulder arthroplasty implants from X-ray images. J Orthop 11:74–78. https://doi.org/10.1016/j.jor.2022.11.004

Article  Google Scholar 

Sivari E, Guzel MS, Bostanci E, Mishra A (2022) A novel hybrid machine learning based system to classify shoulder implant manufacturers. Healthc (Basel) 10:580. https://doi.org/10.3390/healthcare10030580

Article  Google Scholar 

Yang L, Oeding JF, de Marinis R, Marigi E, Sanchez-Sotelo J (2024) Deep learning to automatically classify very large sets of preoperative and postoperative shoulder arthroplasty radiographs. J Shoulder Elb Surg 33:773–780. https://doi.org/10.1016/j.jse.2023.09.021

Article  Google Scholar 

Sekachev B, Manovich N, Zhiltsov M, Zhavoronkov A, Kalinin D, Hoff B et al (2020) opencv/cvat: v1.1.0 [Internet]. https://doi.org/10.5281/zenodo.4009388

Youderian AR, Ricchetti ET, Drews M, Iannotti JP (2014) Determination of humeral head size in anatomic shoulder replacement for glenohumeral osteoarthritis. J Shoulder Elb Surg 23:955–963. https://doi.org/10.1016/j.jse.2013.09.005

Article  Google Scholar 

Fei-Fei L, Deng J, Russakovsky O, Berg A, Li K (2020) ImageNet [Internet]. In. Stanford Vision Lab, Stanford University, Princeton University. https://image-net.org/about.php

He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Xplore, Las Vegas, NV. pp. 770–778. https://doi.org/10.1109/CVPR.2016.90

Huang G, Liu Z, Van Der Maaten L, Wienberger K (2017) Densely connected convolutional networks. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Explore, Honolulu, HI. pp. 2261–2269. https://doi.org/10.1109/CVPR.2017.243

Tan M, Le QV (revised 2020) EfficientNet: Rethinking model scaling for convolutional neural networks. In: 2019 International Conference on Machine Learning. https://doi.org/10.485550/arXiv.1905.11946

Pytorch Pytorch Vision AlexNet [Internet ],accessed 2024. https://pytorch.org/hub/pytorch_vision_alexnet/

Robertson DD, Sharma GB, McMahon PJ, Karas SG (2022) Glenoid version assessment when the CT field of view does not permit the Friedman Method: the Robertson Method. Orthop J Sports Med 10:23259671221083589. https://doi.org/10.1177/23259671221083589

Article  PubMed  PubMed Central  Google Scholar 

Buda M, Saha A, Mazurowski MA (2019) Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm. Comput Biol Med 109:218–225. https://doi.org/10.1016/j.compbiomed.2019.05.002

Article  PubMed  CAS  Google Scholar 

Poplin R, Varadarajan AV, Blumer K, Liu Y, McConnell MV, Corrado GS, Peng L, Webster DR (2018) Rediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat Biomed Eng 2:158–164. https://doi.org/10.1038/s41551-018-0195-0

Article  PubMed  Google Scholar 

Rajpurkar P, Irvin J, Ball RL, Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz CP, Patel BN, Yeom KW, Shpanskaya K, Blankenberg FG, Seekins J, Amrhein TJ, Mong D, Halabi SS, Zucker EJ, Ng AY, Lungren MP (2018) Deep learning for chest radiograph diagnosis: a retrospective comparison of the CheXNeXt algorithm to practicing radiologists. PLoS Med 15:e1002686. https://doi.org/10.1371/journal.pmed.1002686

Article  PubMed  PubMed Central  Google Scholar 

Kunze KN, Jang SJ, Li TY, Pareek A, Finocchiaro A, Fu MC, Tayloer SA, Dines JS, Dines DM, Warren RF, Gulotta LV (2023) Artificial intelligence for automated identification of total shoulder arthroplasty implants. J Shoulder Elb Surg 32:2115–2122. https://doi.org/10.1016/j.jse.2023.03.028

Article  Google Scholar 

留言 (0)

沒有登入
gif