Published on Tue Apr 02 2019

A Strong Baseline for Domain Adaptation and Generalization in Medical Imaging

Li Yao, Jordan Prosky, Ben Covington, Kevin Lyman

This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging. We empirically demonstrate the benefits of training medical imaging deep learning models on varied patient populations.

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Abstract

This work provides a strong baseline for the problem of multi-source multi-target domain adaptation and generalization in medical imaging. Using a diverse collection of ten chest X-ray datasets, we empirically demonstrate the benefits of training medical imaging deep learning models on varied patient populations for generalization to out-of-sample domains.