A semi-supervised multiview-MRI network for the detection of Knee Osteoarthritis - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue Computerized Medical Imaging and Graphics Année : 2024

A semi-supervised multiview-MRI network for the detection of Knee Osteoarthritis

Résumé

Knee OsteoArthritis (OA) is a prevalent chronic condition, affecting a significant proportion of the global population. Detecting knee OA is crucial as the degeneration of the knee joint is irreversible. In this paper, we introduce a semi-supervised multi-view framework and a 3D CNN model for detecting knee OA using 3D Magnetic Resonance Imaging (MRI) scans. We introduce a semi-supervised learning approach combining labeled and unlabeled data to improve the performance and generalizability of the proposed model. Experimental results show the efficacy of our proposed approach in detecting knee OA from 3D MRI scans using a large cohort of 4297 subjects. An ablation study was conducted to investigate the contributions of various components of the proposed model, providing insights into the optimal design of the model. Our results indicate the potential of the proposed approach to improve the accuracy and efficiency of OA diagnosis. The proposed framework reported an AUC of 93.20% for the detection of knee OA.
Fichier non déposé

Dates et versions

hal-04560441 , version 1 (26-04-2024)

Licence

Paternité

Identifiants

Citer

Mohamed Berrimi, Didier Hans, Rachid Jennane. A semi-supervised multiview-MRI network for the detection of Knee Osteoarthritis. Computerized Medical Imaging and Graphics, 2024, 114, pp.102371. ⟨10.1016/j.compmedimag.2024.102371⟩. ⟨hal-04560441⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More