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Current applications and future directions of deep learning in musculoskeletal radiology.

Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, which can be conceptually divided into the categori...

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Published in:Skeletal Radiology Vol. 49; no. 2; pp. 183 - 198
Main Authors: Chea, Pauley, Mandell, Jacob C.
Format: review Journal Article
Published: Springer Nature Feb2020
Online Access:View this record in EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Current applications and future directions of deep learning in musculoskeletal radiology.
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        au:
          Chea, Pauley
          Mandell, Jacob C.
        affil: Division of Musculoskeletal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
      sug:
        subj:
          Diagnostic Imaging Methods
          Image Interpretation, Computer Assisted Methods
          Musculoskeletal Diseases
          Musculoskeletal System
          Specialties, Medical Methods
          Impact of Events Scale
      ab: Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, which can be conceptually divided into the categories of lesion detection, classification, segmentation, and non-interpretive tasks. Numerous examples of deep learning achieving expert-level performance in specific tasks in all four categories have been demonstrated in the past few years, although comprehensive interpretation of imaging examinations has not yet been achieved. It is important for the practicing musculoskeletal radiologist to understand the current scope of deep learning as it relates to musculoskeletal radiology. Interest in deep learning from researchers, radiology leadership, and industry continues to increase, and it is likely that these developments will impact the daily practice of musculoskeletal radiology in the near future.
      pubtype: Academic Journal
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        review
        Journal Article
      ougenre: Article
    language: English
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