Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise

Author:

Mehrtens Hendrik A.ORCID,Kurz AlexanderORCID,Bucher Tabea-ClaraORCID,Brinker Titus J.ORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference46 articles.

1. Optuna: A next-generation hyperparameter optimization framework;Akiba,2019

2. Pitfalls of in-domain uncertainty estimation and ensembling in deep learning;Ashukha,2020

3. Ayhan, M.S., Berens, P., 2018. Test-Time Data Augmentation for Estimation of Heteroscedastic Aleatoric Uncertainty in Deep Neural Networks. In: Proceedings of the First Conference on Medical Imaging with Deep Learning. p. 9.

4. Expert-validated estimation of diagnostic uncertainty for deep neural networks in diabetic retinopathy detection;Ayhan;Med. Image Anal.,2020

5. Benchmarking bayesian deep learning on diabetic retinopathy detection tasks;Band,2021

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1. Pitfalls of Conformal Predictions for Medical Image Classification;Uncertainty for Safe Utilization of Machine Learning in Medical Imaging;2023

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