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Towards increased trustworthiness of deep learning segmentation methods
  on cardiac MRI

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI

27 September 2018
Jörg Sander
B. D. de Vos
J. Wolterink
Ivana Išgum
ArXivPDFHTML

Papers citing "Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI"

17 / 17 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
Uncertainty and Prediction Quality Estimation for Semantic Segmentation
  via Graph Neural Networks
Uncertainty and Prediction Quality Estimation for Semantic Segmentation via Graph Neural Networks
Edgar Heinert
Stephan Tilgner
Timo Palm
Matthias Rottmann
UQCV
49
0
0
17 Sep 2024
Assessment of Deep Learning Segmentation for Real-Time Free-Breathing
  Cardiac Magnetic Resonance Imaging at Rest and Under Exercise Stress
Assessment of Deep Learning Segmentation for Real-Time Free-Breathing Cardiac Magnetic Resonance Imaging at Rest and Under Exercise Stress
Martin Schilling
C. Unterberg-Buchwald
J. Lotz
M. Uecker
31
4
0
23 Nov 2023
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can
  trust
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust
Benjamin Lambert
Florence Forbes
Senan Doyle
A. Tucholka
M. Dojat
UQCV
MedIm
14
6
0
22 Sep 2022
Influence of uncertainty estimation techniques on false-positive
  reduction in liver lesion detection
Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection
Ishaan Bhat
J. Pluim
M. Viergever
Hugo J. Kuijf
MedIm
21
4
0
22 Jun 2022
Maximum Entropy on Erroneous Predictions (MEEP): Improving model
  calibration for medical image segmentation
Maximum Entropy on Erroneous Predictions (MEEP): Improving model calibration for medical image segmentation
Agostina J. Larrazabal
Cesar E. Martínez
Jose Dolz
Enzo Ferrante
19
15
0
22 Dec 2021
Automatic quality control framework for more reliable integration of
  machine learning-based image segmentation into medical workflows
Automatic quality control framework for more reliable integration of machine learning-based image segmentation into medical workflows
Elena Williams
Sebastian Niehaus
J. Reinelt
A. Merola
P. Mihai
...
Evelyn Medawar
Daniel Lichterfeld
Ingo Roeder
N. Scherf
Maria del C. Valdés Hernández
26
3
0
06 Dec 2021
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty
  Propagation in Encoder-Decoder Networks
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks
Giuseppina Carannante
Dimah Dera
Nidhal C.Bouaynaya
Hassan M. Fathallah-Shaykh
Ghulam Rasool
UQCV
AAML
OOD
27
6
0
10 Nov 2021
Calibrating the Dice loss to handle neural network overconfidence for
  biomedical image segmentation
Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation
Michael Yeung
L. Rundo
Yang Nan
Evis Sala
Carola-Bibiane Schönlieb
Guang Yang
UQCV
25
30
0
31 Oct 2021
Recent Advances in Fibrosis and Scar Segmentation from Cardiac MRI: A
  State-of-the-Art Review and Future Perspectives
Recent Advances in Fibrosis and Scar Segmentation from Cardiac MRI: A State-of-the-Art Review and Future Perspectives
Yinzhe Wu
Zeyu Tang
Binghuan Li
D. Firmin
Guang Yang
27
40
0
28 Jun 2021
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Orthogonal Ensemble Networks for Biomedical Image Segmentation
Agostina J. Larrazabal
Cesar E. Martínez
Jose Dolz
Enzo Ferrante
UQCV
18
22
0
22 May 2021
Automatic segmentation with detection of local segmentation failures in
  cardiac MRI
Automatic segmentation with detection of local segmentation failures in cardiac MRI
Jörg Sander
B. D. de Vos
Ivana Išgum
12
50
0
13 Nov 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution
  Datasets
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets
Zhihui Shao
Jianyi Yang
Shaolei Ren
OODD
35
11
0
16 Jun 2020
Confidence Calibration and Predictive Uncertainty Estimation for Deep
  Medical Image Segmentation
Confidence Calibration and Predictive Uncertainty Estimation for Deep Medical Image Segmentation
Alireza Mehrtash
W. Wells
C. Tempany
Purang Abolmaesumi
Tina Kapur
OOD
FedML
UQCV
24
264
0
29 Nov 2019
Deep learning for cardiac image segmentation: A review
Deep learning for cardiac image segmentation: A review
Chia-Ju Chen
C. Qin
Huaqi Qiu
G. Tarroni
Jinming Duan
Wenjia Bai
Daniel Rueckert
SSeg
3DV
64
674
0
09 Nov 2019
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
5,675
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
9,145
0
06 Jun 2015
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