[HTML][HTML] Radiomics and deep learning for disease detection in musculoskeletal radiology: an overview of novel MRI-and CT-based approaches

B Fritz, HY Paul, R Kijowski, J Fritz - Investigative radiology, 2023‏ - journals.lww.com
Radiomics and machine learning–based methods offer exciting opportunities for improving
diagnostic performance and efficiency in musculoskeletal radiology for various tasks …

AI applications in musculoskeletal imaging: a narrative review

S Gitto, F Serpi, D Albano, G Risoleo, S Fusco… - European Radiology …, 2024‏ - Springer
This narrative review focuses on clinical applications of artificial intelligence (AI) in
musculoskeletal imaging. A range of musculoskeletal disorders are discussed using a …

Primary bone tumor detection and classification in full-field bone radiographs via YOLO deep learning model

J Li, S Li, X Li, S Miao, C Dong, C Gao, X Liu, D Hao… - European …, 2023‏ - Springer
Objectives Automatic bone lesions detection and classifications present a critical challenge
and are essential to support radiologists in making an accurate diagnosis of bone lesions. In …

The role of artificial intelligence in anterior cruciate ligament injuries: current concepts and future perspectives

L Andriollo, A Picchi, R Sangaletti, L Perticarini… - Healthcare, 2024‏ - mdpi.com
The remarkable progress in data aggregation and deep learning algorithms has positioned
artificial intelligence (AI) and machine learning (ML) to revolutionize the field of medicine. AI …

Application of artificial intelligence to the public health education

X Wang, X He, J Wei, J Liu, Y Li, X Liu - Frontiers in public health, 2023‏ - frontiersin.org
With the global outbreak of coronavirus disease 2019 (COVID-19), public health has
received unprecedented attention. The cultivation of emergency and compound …

[HTML][HTML] Advanced magnetic resonance imaging (MRI) techniques: technical principles and applications in nanomedicine

F Bruno, V Granata, F Cobianchi Bellisari, F Sgalambro… - Cancers, 2022‏ - mdpi.com
Simple Summary Magnetic Resonance Imaging (MRI) is a consolidated imaging tool for the
multiparametric assessment of tissues in various pathologies from degenerative and …

Deep learning diagnosis and classification of rotator cuff tears on shoulder MRI

DJ Lin, M Schwier, B Geiger, E Raithel… - Investigative …, 2023‏ - journals.lww.com
Background Detection of rotator cuff tears, a common cause of shoulder disability, can be
time-consuming and subject to reader variability. Deep learning (DL) has the potential to …

Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI

J Yao, L Chepelev, Y Nisha, P Sathiadoss, FJ Rybicki… - Skeletal Radiology, 2022‏ - Springer
Objective To evaluate if deep learning is a feasible approach for automated detection of
supraspinatus tears on MRI. Materials and methods A total of 200 shoulder MRI studies …

The role of imaging in osteoarthritis

EH Park, J Fritz - Best Practice & Research Clinical Rheumatology, 2023‏ - Elsevier
Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and
physiologic derangement. Advances in imaging techniques have expanded the role of …

Performance of a deep convolutional neural network for MRI-based vertebral body measurements and insufficiency fracture detection

C Germann, AN Meyer, M Staib, R Sutter, B Fritz - European Radiology, 2023‏ - Springer
Objectives The aim is to validate the performance of a deep convolutional neural network
(DCNN) for vertebral body measurements and insufficiency fracture detection on lumbar …