Deep Learning–based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses-Reference-Cited by-同舟云学术

Deep Learning–based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses

Published:2019-08 Issue:2 Volume:292 Page:365-373
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Choe Jooae¹^ORCID,Lee Sang Min¹^ORCID,Do Kyung-Hyun¹^ORCID,Lee Gaeun¹^ORCID,Lee June-Goo¹^ORCID,Lee Sang Min¹^ORCID,Seo Joon Beom¹^ORCID

Affiliation:

1. From the Department of Radiology and Research Institute of Radiology (J.C., S.M.L.[1], K.H.D., S.M.L.[2], J.B.S.) and Department of Convergence Medicine (G.L., J.G.L.), University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-ro 43 Gil, Songpa-gu, Seoul 138-736, Korea.

Funder

National Research Foundation of Korea

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2019181960

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3. Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing