How inter-rater variability relates to aleatoric and epistemic uncertainty: a case study with deep learning-based paraspinal muscle segmentation

14 August 2023

Papers citing "How inter-rater variability relates to aleatoric and epistemic uncertainty: a case study with deep learning-based paraspinal muscle segmentation"

6 / 6 papers shown

Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation M. Valiuddin R. V. Sloun C.G.A. Viviers Peter H. N. de With Fons van der Sommen UQCV 96 1 0 25 Nov 2024
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis Benjamin Lambert Florence Forbes A. Tucholka Senan Doyle Harmonie Dehaene M. Dojat 34 81 0 05 Oct 2022
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation Robin Camarasa D. Bos J. Hendrikse P. Nederkoorn D. Epidemiology D. Neurology Department of Computer Science UQCV 29 12 0 22 Sep 2021
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging M. Laves Sontje Ihler J. F. Fast L. Kahrs T. Ortmaier OOD UQCV BDL 43 29 0 26 Apr 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,695 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 287 9,167 0 06 Jun 2015