Convolutional Neural Network Addresses the Confounding Impact of CT Reconstruction Kernels on Radiomics Studies

Yoon, J. H., Sun, S. H., Xiao, M., Yang, H., Lu, L., Li, Y., Schwartz, L. H., & Zhao, B. (2021). Convolutional Neural Network Addresses the Confounding Impact of CT Reconstruction Kernels on Radiomics Studies. Tomography, 7(4), 877–892. https://doi.org/10.3390/tomography7040074
Authors:
Jin H Yoon
Shawn H Sun
Manjun Xiao
Hao Yang
Lin Lu
Yajun Li
Lawrence H Schwartz
Binsheng Zhao
Affiliated Authors:
Jin H Yoon
Shawn H Sun
Hao Yang
Lin Lu
Lawrence H Schwartz
Binsheng Zhao
Columbia Affiliation:
Subjects:
Lung Neoplasms (MeSH)
Tomography, X-Ray Computed (MeSH)
Author Keywords:
radiomics
reproducibility
convolutional neural network
computed tomography
kernel conversion
quantitative imaging
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Publication Type:
Article
Unique ID:
10.3390/tomography7040074
PMID:
34941646
DOI:
10.3390/tomography7040074
Journal:
Tomography
Publication Date:
Data Source:
PubMed
Source Link:
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