Publisher
Springer Nature Switzerland
Reference26 articles.
1. Lecture Notes in Computer Science;V Arsigny,2006
2. Bashyam, V.M., et al.: The iSTAGING and PHENOM consortia: deep generative medical image harmonization for improving cross-site generalization in deep learning predictors. J. Magn. Reson. Imaging 55(3), 908–916 (2022)
3. Bernhardt, M., Jones, C., Glocker, B.: Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms. Nat. Med. 28(6), 1157–1158 (2022)
4. Castro, D.C., Tan, J., Kainz, B., Konukoglu, E., Glocker, B.: Morpho-MNIST: quantitative assessment and diagnostics for representation learning. J. Mach. Learn. Res. 20, 1–29 (2019)
5. Dinsdale, N.K., Jenkinson, M., Namburete, A.I.L.: Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal. Neuroimage 228, 117689 (2021)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献