DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks

Shi Yan; Taghi Ramazanian; Elham Sagheb; Sunyang Fu; Sunghwan Sohn; David G. Lewallen; Hongfang Liu; Walter K. Kremers; Vipin Chaudhary; Michael Taunton; Hilal Maradit Kremers; Ahmad P. Tafti

doi:10.1007/978-3-030-64559-5_12

DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks

Shi Yan, Taghi Ramazanian, Elham Sagheb, Sunyang Fu, Sunghwan Sohn, David G. Lewallen, Hongfang Liu, Walter K. Kremers, Vipin Chaudhary, Michael Taunton, Hilal Maradit Kremers, Ahmad P. Tafti

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Total knee arthroplasty (TKA) is one of the most successful surgical procedures worldwide. It improves quality of life, mobility, and functionality for the vast majority of patients. However, a TKA surgery may fail over time for several reasons, thus it requires a revision arthroplasty surgery. Identifying TKA implants is a critical consideration in preoperative planning of revision surgery. This study aims to develop, train, and validate deep convolutional neural network models to precisely classify four widely-used TKA implants based on only plain knee radiographs. Using 9,052 computationally annotated knee radiographs, we achieved weighted average precision, recall, and F1-score of 0.97, 0.97, and 0.97, respectively, with Cohen Kappa of 0.96.

Original language	English (US)
Title of host publication	Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings
Editors	George Bebis, Zhaozheng Yin, Edward Kim, Jan Bender, Kartic Subr, Bum Chul Kwon, Jian Zhao, Denis Kalkofen, George Baciu
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	154-165
Number of pages	12
ISBN (Print)	9783030645588
DOIs	https://doi.org/10.1007/978-3-030-64559-5_12
State	Published - 2020
Event	15th International Symposium on Visual Computing, ISVC 2020 - San Diego, United States Duration: Oct 5 2020 → Oct 7 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12510 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th International Symposium on Visual Computing, ISVC 2020
Country/Territory	United States
City	San Diego
Period	10/5/20 → 10/7/20

Keywords

Deep learning
Knee radiographs
Total knee arthroplasty

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-64559-5_12

Cite this

Yan, S., Ramazanian, T., Sagheb, E., Fu, S., Sohn, S., Lewallen, D. G., Liu, H., Kremers, W. K., Chaudhary, V., Taunton, M., Kremers, H. M., & Tafti, A. P. (2020). DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. In G. Bebis, Z. Yin, E. Kim, J. Bender, K. Subr, B. C. Kwon, J. Zhao, D. Kalkofen, & G. Baciu (Eds.), Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings (pp. 154-165). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12510 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-64559-5_12

DeepTKAClassifier : Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. / Yan, Shi; Ramazanian, Taghi; Sagheb, Elham et al.

Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings. ed. / George Bebis; Zhaozheng Yin; Edward Kim; Jan Bender; Kartic Subr; Bum Chul Kwon; Jian Zhao; Denis Kalkofen; George Baciu. Springer Science and Business Media Deutschland GmbH, 2020. p. 154-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12510 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yan, S, Ramazanian, T, Sagheb, E, Fu, S, Sohn, S, Lewallen, DG, Liu, H , Kremers, WK, Chaudhary, V, Taunton, M, Kremers, HM & Tafti, AP 2020, DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. in G Bebis, Z Yin, E Kim, J Bender, K Subr, BC Kwon, J Zhao, D Kalkofen & G Baciu (eds), Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12510 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 154-165, 15th International Symposium on Visual Computing, ISVC 2020, San Diego, United States, 10/5/20. https://doi.org/10.1007/978-3-030-64559-5_12

Yan S, Ramazanian T, Sagheb E, Fu S, Sohn S, Lewallen DG et al. DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. In Bebis G, Yin Z, Kim E, Bender J, Subr K, Kwon BC, Zhao J, Kalkofen D, Baciu G, editors, Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 154-165. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-64559-5_12

Yan, Shi ; Ramazanian, Taghi ; Sagheb, Elham et al. / DeepTKAClassifier : Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks. Advances in Visual Computing - 15th International Symposium, ISVC 2020, Proceedings. editor / George Bebis ; Zhaozheng Yin ; Edward Kim ; Jan Bender ; Kartic Subr ; Bum Chul Kwon ; Jian Zhao ; Denis Kalkofen ; George Baciu. Springer Science and Business Media Deutschland GmbH, 2020. pp. 154-165 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Total knee arthroplasty (TKA) is one of the most successful surgical procedures worldwide. It improves quality of life, mobility, and functionality for the vast majority of patients. However, a TKA surgery may fail over time for several reasons, thus it requires a revision arthroplasty surgery. Identifying TKA implants is a critical consideration in preoperative planning of revision surgery. This study aims to develop, train, and validate deep convolutional neural network models to precisely classify four widely-used TKA implants based on only plain knee radiographs. Using 9,052 computationally annotated knee radiographs, we achieved weighted average precision, recall, and F1-score of 0.97, 0.97, and 0.97, respectively, with Cohen Kappa of 0.96.",

keywords = "Deep learning, Knee radiographs, Total knee arthroplasty",

author = "Shi Yan and Taghi Ramazanian and Elham Sagheb and Sunyang Fu and Sunghwan Sohn and Lewallen, {David G.} and Hongfang Liu and Kremers, {Walter K.} and Vipin Chaudhary and Michael Taunton and Kremers, {Hilal Maradit} and Tafti, {Ahmad P.}",

note = "Funding Information: Acknowledgment. This work was supported by the National Institutes of Health (NIH) grants R01AR73147 and P30AR76312. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 15th International Symposium on Visual Computing, ISVC 2020 ; Conference date: 05-10-2020 Through 07-10-2020",

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N1 - Funding Information: Acknowledgment. This work was supported by the National Institutes of Health (NIH) grants R01AR73147 and P30AR76312. Publisher Copyright: © 2020, Springer Nature Switzerland AG.

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Y1 - 2020

N2 - Total knee arthroplasty (TKA) is one of the most successful surgical procedures worldwide. It improves quality of life, mobility, and functionality for the vast majority of patients. However, a TKA surgery may fail over time for several reasons, thus it requires a revision arthroplasty surgery. Identifying TKA implants is a critical consideration in preoperative planning of revision surgery. This study aims to develop, train, and validate deep convolutional neural network models to precisely classify four widely-used TKA implants based on only plain knee radiographs. Using 9,052 computationally annotated knee radiographs, we achieved weighted average precision, recall, and F1-score of 0.97, 0.97, and 0.97, respectively, with Cohen Kappa of 0.96.

AB - Total knee arthroplasty (TKA) is one of the most successful surgical procedures worldwide. It improves quality of life, mobility, and functionality for the vast majority of patients. However, a TKA surgery may fail over time for several reasons, thus it requires a revision arthroplasty surgery. Identifying TKA implants is a critical consideration in preoperative planning of revision surgery. This study aims to develop, train, and validate deep convolutional neural network models to precisely classify four widely-used TKA implants based on only plain knee radiographs. Using 9,052 computationally annotated knee radiographs, we achieved weighted average precision, recall, and F1-score of 0.97, 0.97, and 0.97, respectively, with Cohen Kappa of 0.96.

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ER -

DeepTKAClassifier: Brand Classification of Total Knee Arthroplasty Implants Using Explainable Deep Convolutional Neural Networks

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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