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Improved post-hoc probability calibration for out-of-domain MRI
  segmentation

Improved post-hoc probability calibration for out-of-domain MRI segmentation

4 August 2022
C. Ouyang
Shuo Wang
C. L. P. Chen
Zeju Li
Wenjia Bai
Bernhard Kainz
Daniel Rueckert
    UQCV
    MedIm
ArXivPDFHTML

Papers citing "Improved post-hoc probability calibration for out-of-domain MRI segmentation"

7 / 7 papers shown
Title
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical
  Image Segmentation
Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation
P. Mody
Nicolas F. Chaves-de-Plaza
Chinmay Rao
Eleftheria Astrenidou
M. de Ridder
N. Hoekstra
Klaus Hildebrandt
Marius Staring
UQCV
22
0
0
05 Sep 2024
Comparative Benchmarking of Failure Detection Methods in Medical Image
  Segmentation: Unveiling the Role of Confidence Aggregation
Comparative Benchmarking of Failure Detection Methods in Medical Image Segmentation: Unveiling the Role of Confidence Aggregation
M. Zenk
David Zimmerer
Fabian Isensee
Jeremias Traub
T. Norajitra
Paul F. Jäger
Klaus H. Maier-Hein
37
4
0
05 Jun 2024
Mask-TS Net: Mask Temperature Scaling Uncertainty Calibration for Polyp
  Segmentation
Mask-TS Net: Mask Temperature Scaling Uncertainty Calibration for Polyp Segmentation
Yudian Zhang
Chenhao Xu
Kaiye Xu
Haijiang Zhu
41
0
0
09 May 2024
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications
  to Cardiac MRI Segmentation
Bayesian Uncertainty Estimation by Hamiltonian Monte Carlo: Applications to Cardiac MRI Segmentation
Yidong Zhao
João Tourais
Iain Pierce
Christian Nitsche
T. Treibel
Sebastian Weingartner
Artur M. Schweidtmann
Qian Tao
BDL
UQCV
38
5
0
04 Mar 2024
Single-domain Generalization in Medical Image Segmentation via Test-time
  Adaptation from Shape Dictionary
Single-domain Generalization in Medical Image Segmentation via Test-time Adaptation from Shape Dictionary
Quande Liu
Cheng Chen
Qi Dou
Pheng-Ann Heng
OOD
47
36
0
29 Jun 2022
TorchIO: A Python library for efficient loading, preprocessing,
  augmentation and patch-based sampling of medical images in deep learning
TorchIO: A Python library for efficient loading, preprocessing, augmentation and patch-based sampling of medical images in deep learning
Fernando Pérez-García
Rachel Sparks
Sébastien Ourselin
MedIm
LM&MA
135
426
0
09 Mar 2020
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
279
9,136
0
06 Jun 2015
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