3D convolutional neural networks for detection and severity staging of meniscus and PFJ cartilage morphological degenerative changes in osteoarthritis and anterior …
V Pedoia, B Norman, SN Mehany… - Journal of Magnetic …, 2019 - Wiley Online Library
Background Semiquantitative assessment of MRI plays a central role in musculoskeletal
research; however, in the clinical setting MRI reports often tend to be subjective and …
research; however, in the clinical setting MRI reports often tend to be subjective and …
Improved deep convolutional neural network to classify osteoarthritis from anterior cruciate ligament tear using magnetic resonance imaging
Anterior cruciate ligament (ACL) tear is caused by partially or completely torn ACL ligament
in the knee, especially in sportsmen. There is a need to classify the ACL tear before it fully …
in the knee, especially in sportsmen. There is a need to classify the ACL tear before it fully …
Deep learning approach for evaluating knee MR images: achieving high diagnostic performance for cartilage lesion detection
F Liu, Z Zhou, A Samsonov, D Blankenbaker… - Radiology, 2018 - pubs.rsna.org
Purpose To determine the feasibility of using a deep learning approach to detect cartilage
lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due …
lesions (including cartilage softening, fibrillation, fissuring, focal defects, diffuse thinning due …
Automatic deep learning–assisted detection and grading of abnormalities in knee MRI studies
Purpose To test the hypothesis that artificial intelligence (AI) techniques can aid in
identifying and assessing lesion severity in the cartilage, bone marrow, meniscus, and …
identifying and assessing lesion severity in the cartilage, bone marrow, meniscus, and …
Magnetic resonance imaging assessments for knee segmentation and their use in combination with machine/deep learning as predictors of early osteoarthritis …
J Martel-Pelletier, P Paiement… - Therapeutic Advances …, 2023 - journals.sagepub.com
Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over
decades. This disease is heterogeneous and involves structural changes in the whole joint …
decades. This disease is heterogeneous and involves structural changes in the whole joint …
Deep learning‐based segmentation of knee MRI for fully automatic subregional morphological assessment of cartilage tissues: Data from the Osteoarthritis Initiative
Morphological changes in knee cartilage subregions are valuable imaging‐based
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
biomarkers for understanding progression of osteoarthritis, and they are typically detected …
Deep learning for lesion detection, progression, and prediction of musculoskeletal disease
Deep learning is one of the most exciting new areas in medical imaging. This review article
provides a summary of the current clinical applications of deep learning for lesion detection …
provides a summary of the current clinical applications of deep learning for lesion detection …
Use of 2D U-Net convolutional neural networks for automated cartilage and meniscus segmentation of knee MR imaging data to determine relaxometry and …
B Norman, V Pedoia, S Majumdar - Radiology, 2018 - pubs.rsna.org
Purpose To analyze how automatic segmentation translates in accuracy and precision to
morphology and relaxometry compared with manual segmentation and increases the speed …
morphology and relaxometry compared with manual segmentation and increases the speed …
Artificial intelligence for MRI diagnosis of joints: a scoping review of the current state-of-the-art of deep learning-based approaches
Deep learning-based MRI diagnosis of internal joint derangement is an emerging field of
artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A …
artificial intelligence, which offers many exciting possibilities for musculoskeletal radiology. A …
Deep-learning-assisted diagnosis for knee magnetic resonance imaging: development and retrospective validation of MRNet
Background Magnetic resonance imaging (MRI) of the knee is the preferred method for
diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject …
diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject …