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Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI

Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI

30 October 2023
F. Terhag
P. Knechtges
A. Basermann
R. Tempone
ArXivPDFHTML

Papers citing "Uncertainty Quantification in Machine Learning Based Segmentation: A Post-Hoc Approach for Left Ventricle Volume Estimation in MRI"

2 / 2 papers shown
Title
Sparse Bayesian Learning for Label Efficiency in Cardiac Real-Time MRI
Sparse Bayesian Learning for Label Efficiency in Cardiac Real-Time MRI
Felix Terhag
P. Knechtges
A. Basermann
Anja Bach
Darius Gerlach
Jens Tank
Raúl Tempone
40
0
0
27 Mar 2025
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
247
9,042
0
06 Jun 2015
1