Literature DB >> 31163504

Artificial Intelligence in Musculoskeletal Imaging: Review of Current Literature, Challenges, and Trends.

Anna Hirschmann1, Joshy Cyriac1, Bram Stieltjes1, Tobias Kober2,3,4, Jonas Richiardi2,3, Patrick Omoumi2.   

Abstract

Artificial intelligence (AI) has gained major attention with a rapid increase in the number of published articles, mostly recently. This review provides a general understanding of how AI can or will be useful to the musculoskeletal radiologist. After a brief technical background on AI, machine learning, and deep learning, we illustrate, through examples from the musculoskeletal literature, potential AI applications in the various steps of the radiologist's workflow, from managing the request to communication of results. The implementation of AI solutions does not go without challenges and limitations. These are also discussed, as well as the trends and perspectives. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Mesh:

Year:  2019        PMID: 31163504     DOI: 10.1055/s-0039-1684024

Source DB:  PubMed          Journal:  Semin Musculoskelet Radiol        ISSN: 1089-7860            Impact factor:   1.777


  10 in total

1.  Artificial intelligence in musculoskeletal oncological radiology.

Authors:  Matjaz Vogrin; Teodor Trojner; Robi Kelc
Journal:  Radiol Oncol       Date:  2020-11-10       Impact factor: 2.991

Review 2.  Artificial Intelligence Explained for Nonexperts.

Authors:  Narges Razavian; Florian Knoll; Krzysztof J Geras
Journal:  Semin Musculoskelet Radiol       Date:  2020-01-28       Impact factor: 1.777

Review 3.  New insights into the evaluation of peripheral nerves lesions: a survival guide for beginners.

Authors:  Teodoro Martín-Noguerol; Rafael Barousse; Antonio Luna; Mariano Socolovsky; Juan M Górriz; Manuel Gómez-Río
Journal:  Neuroradiology       Date:  2022-02-25       Impact factor: 2.804

Review 4.  AI MSK clinical applications: cartilage and osteoarthritis.

Authors:  Gabby B Joseph; Charles E McCulloch; Jae Ho Sohn; Valentina Pedoia; Sharmila Majumdar; Thomas M Link
Journal:  Skeletal Radiol       Date:  2021-11-04       Impact factor: 2.199

Review 5.  Stakeholders' perspectives on the future of artificial intelligence in radiology: a scoping review.

Authors:  Ling Yang; Ioana Cezara Ene; Reza Arabi Belaghi; David Koff; Nina Stein; Pasqualina Lina Santaguida
Journal:  Eur Radiol       Date:  2021-09-21       Impact factor: 5.315

Review 6.  Musculoskeletal trauma and artificial intelligence: current trends and projections.

Authors:  Olga Laur; Benjamin Wang
Journal:  Skeletal Radiol       Date:  2021-06-05       Impact factor: 2.199

7.  Artificial intelligence in musculoskeletal oncological radiology.

Authors:  Matjaz Vogrin; Teodor Trojner; Robi Kelc
Journal:  Radiol Oncol       Date:  2020-11-10       Impact factor: 2.991

8.  AI-based detection and classification of distal radius fractures using low-effort data labeling: evaluation of applicability and effect of training set size.

Authors:  Patrick Tobler; Joshy Cyriac; Balazs K Kovacs; Verena Hofmann; Raphael Sexauer; Fabiano Paciolla; Bram Stieltjes; Felix Amsler; Anna Hirschmann
Journal:  Eur Radiol       Date:  2021-03-19       Impact factor: 5.315

Review 9.  AI MSK clinical applications: spine imaging.

Authors:  Florian A Huber; Roman Guggenberger
Journal:  Skeletal Radiol       Date:  2021-07-15       Impact factor: 2.199

Review 10.  Rapid Knee MRI Acquisition and Analysis Techniques for Imaging Osteoarthritis.

Authors:  Akshay S Chaudhari; Feliks Kogan; Valentina Pedoia; Sharmila Majumdar; Garry E Gold; Brian A Hargreaves
Journal:  J Magn Reson Imaging       Date:  2019-11-21       Impact factor: 4.813

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.