Physical imaging parameter variation drives domain shift

Abstract Statistical learning algorithms strongly rely on an oversimplified assumption for optimal performance, that is, source (training) and target (testing) data are independent and identically distributed. Variation in human tissue, physician labeling and physical imaging parameters (PIPs) in th...

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Bibliographic Details
Main Authors: Oz Kilim, Alex Olar, Tamás Joó, Tamás Palicz, Péter Pollner, István Csabai
Format: Article
Language:English
Published: Nature Portfolio 2022-12-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-23990-4