Journal
JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY
Volume 44, Issue 2, Pages 161-167Publisher
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/RCT.0000000000000928
Keywords
neural networks (computer); tomography; x-ray computed; machine learning; artificial intelligence; deep learning
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Deep learning (DL), part of a broader family of machine learning methods, is based on learning data representations rather than task-specific algorithms. Deep learning can be used to improve the image quality of clinical scans with image noise reduction. We review the ability of DL to reduce the image noise, present the advantages and disadvantages of computed tomography image reconstruction, and examine the potential value of new DL-based computed tomography image reconstruction.
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