ViVGG19: Novel exemplar deep feature extraction-based shoulder rotator cuff tear and biceps tendinosis detection using magnetic resonance images
Article
Article Title | ViVGG19: Novel exemplar deep feature extraction-based shoulder rotator cuff tear and biceps tendinosis detection using magnetic resonance images |
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ERA Journal ID | 5057 |
Article Category | Article |
Authors | Key, Sefa, Demir, Sukru, Gurger, Murat, Yilmaz, Erhan, Barua, Prabal Datta, Dogan, Sengul, Tuncer, Turker, Arunkumar, N., Tan, Ru-San and Acharya, U Rajendra |
Journal Title | Medical Engineering and Physics |
Journal Citation | 110 |
Article Number | 103864 |
Number of Pages | 9 |
Year | 2022 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 1350-4533 |
1873-4030 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.medengphy.2022.103864 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1350453322001126 |
Abstract | Background and purpose Materials and methods Results Conclusions |
Keywords | Rotator cuff tear detection ; Biceps tendinosis detection ; Deep feature extraction ; ViVGG19; Iterative feature selection ; Machine learning ; Classification |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Ministry of Health, Turkey |
Firat University, Turkey | |
School of Business | |
University of Technology Sydney | |
Rathinam College of Engineering, India | |
National Heart Centre, Singapore | |
Duke-NUS Medical School, Singapore | |
Ngee Ann Polytechnic, Singapore | |
Singapore University of Social Sciences (SUSS), Singapore | |
Asia University, Taiwan |
https://research.usq.edu.au/item/z0238/vivgg19-novel-exemplar-deep-feature-extraction-based-shoulder-rotator-cuff-tear-and-biceps-tendinosis-detection-using-magnetic-resonance-images
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