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Deep Learning Algorithm for Reducing CT Slice Thickness: Effect on Reproducibility of Radiomic Features in Lung Cancer
OBJECTIVE: To retrospectively assess the effect of CT slice thickness on the reproducibility of radiomic features (RFs) of lung cancer, and to investigate whether convolutional neural network (CNN)-based super-resolution (SR) algorithms can improve the reproducibility of RFs obtained from images wit...
Shranjeno v:
| izdano v: | Korean J Radiol |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
The Korean Society of Radiology
2019
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| Teme: | |
| Online dostop: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6757001/ https://ncbi.nlm.nih.gov/pubmed/31544368 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3348/kjr.2019.0212 |
| Oznake: |
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