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

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

14 August 2023
Parinaz Roshanzamir
H. Rivaz
Joshua Ahn
Hamza Mirza
Neda Naghdi
Meagan Anstruther
M. C. Battié
M. Fortin
Yiming Xiao
ArXivPDFHTML

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

5 / 5 papers shown
Title
A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation
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
91
1
0
25 Nov 2024
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to
  Multi-Class Segmentation
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
24
12
0
22 Sep 2021
Recalibration of Aleatoric and Epistemic Regression Uncertainty in
  Medical Imaging
Recalibration of Aleatoric and Epistemic Regression Uncertainty in Medical Imaging
M. Laves
Sontje Ihler
J. F. Fast
L. Kahrs
T. Ortmaier
OOD
UQCV
BDL
30
29
0
26 Apr 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCV
BDL
276
5,660
0
05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1