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Comparison of machine learning-driven lesion classifiers in prostate PET/MRI cases over different repeatability categories of radiomic features
0
Zitationen
5
Autoren
2019
Jahr
Abstract
Various radiomics features in PET were reported to be sensitive to multi-centric imaging variations. Our goal was to compare different Gleason pattern classifiers in prostate PET/MRI studies built on various subsets of radiomic features belonging to different repeatability categories as determined in [1].
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