A transfer learning approach to facilitate ComBat-based harmonization of multicentre radiomic features in new datasets
Abstract
To facilitate the demonstration of the prognostic value of radiomics, multicenter radiomics studies are needed. Pooling radiomic features of such data in a statistical analysis is however challenging, as they are sensitive to the variability in scanner models, acquisition protocols and reconstruction settings, which is often unavoidable in a multicentre retrospective analysis. A statistical harmonization strategy called ComBat was utilized in...
Paper Details
Title
A transfer learning approach to facilitate ComBat-based harmonization of multicentre radiomic features in new datasets
Published Date
Jul 1, 2021
Journal
Volume
16
Issue
7
Pages
e0253653 - e0253653
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