Deep Feature Stability Analysis Using CT Images of a Physical Phantom Across Scanner Manufacturers, Cartridges, Pixel Sizes, and Slice Thickness.
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SUBMITTER: Paul R
PROVIDER: S-EPMC7289258 | biostudies-literature | 2020 Jun
REPOSITORIES: biostudies-literature
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Deep Feature Stability Analysis Using CT Images of a Physical Phantom Across Scanner Manufacturers, Cartridges, Pixel Sizes, and Slice Thickness.
Paul Rahul R Shafiq-Ul Hassan Mohammed M Moros Eduardo G EG Gillies Robert J RJ Hall Lawrence O LO Goldgof Dmitry B DB
Tomography (Ann Arbor, Mich.) 20200601 2
Image acquisition parameters for computed tomography scans such as slice thickness and field of view may vary depending on tumor size and site. Recent studies have shown that some radiomics features were dependent on voxel size (= pixel size × slice thickness), and with proper normalization, this voxel size dependency could be reduced. Deep features from a convolutional neural network (CNN) have shown great promise in characterizing cancers. However, how do these deep features vary with changes ...[more]
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