Detection and Classification of Knee Injuries from MR Images Using the MRNet Dataset with Progressively Operating Deep Learning Methods

Detection and Classification of Knee Injuries from MR Images Using the MRNet Dataset with Progressively Operating Deep Learning Methods

This study aimed to build progressively operating deep learning models that could detect meniscus injuries, anterior cruciate ligament (ACL) tears and knee abnormalities in magnetic resonance imaging (MRI). The Stanford Machine Learning Group MRNet dataset was employed in the study, which included M...

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Bibliographic Details
Main Authors: Ali Can Kara, Fırat Hardalaç
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Machine Learning and Knowledge Extraction
Subjects:
deep learning
transfer learning
ResNet50
convolutional neural networks
denoising autoencoders
knee injuries
Online Access:https://www.mdpi.com/2504-4990/3/4/50

Internet

https://www.mdpi.com/2504-4990/3/4/50

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