About this Research Topic
Novel imaging, image processing, and image analysis techniques have a great potential to enable earlier diagnosis and deeper understanding of musculoskeletal disorders and pathophysiological processes related to them. This would also enable development and application of relevant treatment in the early phases of the diseases when they might be more amenable to modification. In addition to the novel MRI techniques, novel imaging modalities such as Spectral CT or photon-counting CT and PET/MR may provide more detailed view of the joint. Artificial intelligence (AI) techniques have a great potential to enhance each component in the imaging chain.
This Research Topic aims to present applications of novel and innovative imaging, image processing, and image analysis techniques on assessment of musculoskeletal disorders and pathophysiological processes behind them. We welcome the submission of any manuscript type supported by Frontiers in Physiology (including original research and review articles) covering, but not limited to the following topics:
• AI in musculoskeletal imaging
• Imaging of physiological processes
• Imaging biomarkers
• Quantitative MRI
• Novel imaging modalities such as spectral CT or photon-counting CT and PET/MR and ultrasound
• Prediction of musculoskeletal disorders using image data
Dr. Simo Saarakkala receives financial compensation for his role as Associate Editor of Osteoarthritis and Cartilage Open, a journal published by Elsevier and managed by Osteoarthritis Research Society International (OARSI). All other Topics Editors declare no Conflicts of Interest
Keywords: Musculoskeletal Imaging, Machine Learning, Deep Learning, Musculoskeletal Disorders, Image Analysis, Imaging Biomarker, Joint, Osteoarthritis, Osteoporosis
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.