Possibility of Deep Learning in Medical Imaging Focusing Improvement of Computed Tomography Image Quality.
Journal
Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942
Informations de publication
Date de publication:
Historique:
pubmed:
4
12
2019
medline:
2
4
2020
entrez:
3
12
2019
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 31789682
doi: 10.1097/RCT.0000000000000928
pii: 00004728-202003000-00001
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
161-167Références
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