Your browser doesn't support javascript.
loading
Possibility of Deep Learning in Medical Imaging Focusing Improvement of Computed Tomography Image Quality.
Nakamura, Yuko; Higaki, Toru; Tatsugami, Fuminari; Honda, Yukiko; Narita, Keigo; Akagi, Motonori; Awai, Kazuo.
Affiliation
  • Nakamura Y; From the Diagnostic Radiology, Hiroshima University, Hiroshima, Japan.
J Comput Assist Tomogr ; 44(2): 161-167, 2020.
Article in En | MEDLINE | ID: mdl-31789682
Subject(s)
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Database: MEDLINE Main subject: Radiographic Image Interpretation, Computer-Assisted / Tomography, X-Ray Computed / Quality Improvement / Deep Learning Limits: Humans Language: En Journal: J Comput Assist Tomogr Year: 2020 Type: Article Affiliation country: Japan
Fulltext
Add to My VHL
Print
XML
PubMed Links
Search on Google

Full text: 1 Database: MEDLINE Main subject: Radiographic Image Interpretation, Computer-Assisted / Tomography, X-Ray Computed / Quality Improvement / Deep Learning Limits: Humans Language: En Journal: J Comput Assist Tomogr Year: 2020 Type: Article Affiliation country: Japan