ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.05978
  4. Cited By
SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty
  Propagation in Encoder-Decoder Networks
v1v2v3 (latest)

SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks

10 November 2021
Giuseppina Carannante
Dimah Dera
Nidhal C.Bouaynaya
Hassan M. Fathallah-Shaykh
Ghulam Rasool
    UQCVAAMLOOD
ArXiv (abs)PDFHTML

Papers citing "SUPER-Net: Trustworthy Medical Image Segmentation with Uncertainty Propagation in Encoder-Decoder Networks"

34 / 34 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
271
1
0
25 Nov 2024
Robust Learning via Ensemble Density Propagation in Deep Neural Networks
Robust Learning via Ensemble Density Propagation in Deep Neural Networks
Giuseppina Carannante
Dimah Dera
Ghulam Rasool
N. Bouaynaya
Lyudmila Mihaylova
AAMLMDE
59
5
0
10 Nov 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
73
22
0
22 May 2021
Objective Evaluation of Deep Uncertainty Predictions for COVID-19
  Detection
Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection
Hamzeh Asgharnezhad
Afshar Shamsi Jokandan
R. Alizadehsani
Abbas Khosravi
S. Nahavandi
Z. Sani
D. Srinivasan
UQCV
75
72
0
22 Dec 2020
A survey of loss functions for semantic segmentation
A survey of loss functions for semantic segmentation
Shruti Jadon
SSeg
107
845
0
26 Jun 2020
Bayesian Neural Networks: An Introduction and Survey
Bayesian Neural Networks: An Introduction and Survey
Ethan Goan
Clinton Fookes
BDLUQCV
76
208
0
22 Jun 2020
Uncertainty Evaluation Metric for Brain Tumour Segmentation
Uncertainty Evaluation Metric for Brain Tumour Segmentation
Raghav Mehta
Angelos Filos
Y. Gal
Tal Arbel
UQCV
73
16
0
28 May 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
OODFedMLUQCV
138
275
0
29 Nov 2019
Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical
  Image Segmentation
Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation
Maria G. Baldeon Calisto
S. Lai-Yuen
66
16
0
26 Jul 2019
PHiSeg: Capturing Uncertainty in Medical Image Segmentation
PHiSeg: Capturing Uncertainty in Medical Image Segmentation
Christian F. Baumgartner
K. Tezcan
K. Chaitanya
A. Hötker
Urs J. Muehlematter
K. Schawkat
Anton S. Becker
O. Donati
E. Konukoglu
UQCV
86
204
0
07 Jun 2019
A large annotated medical image dataset for the development and
  evaluation of segmentation algorithms
A large annotated medical image dataset for the development and evaluation of segmentation algorithms
Amber L. Simpson
Michela Antonelli
Spyridon Bakas
Michel Bilello
Keyvan Farahani
...
M. McHugo
S. Napel
Eugene Vorontsov
Lena Maier-Hein
M. Jorge Cardoso
120
862
0
25 Feb 2019
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall
  Survival Prediction using Radiomic Features
Brain Tumor Segmentation using an Ensemble of 3D U-Nets and Overall Survival Prediction using Radiomic Features
Xue Feng
Nicholas J. Tustison
C. Meyer
69
224
0
03 Dec 2018
Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation
  for Structure-wise Quality Control
Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control
Abhijit Guha Roy
Sailesh Conjeti
Nassir Navab
Christian Wachinger
UQCV
73
120
0
24 Nov 2018
Towards increased trustworthiness of deep learning segmentation methods
  on cardiac MRI
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI
Jörg Sander
B. D. de Vos
J. Wolterink
Ivana Išgum
55
59
0
27 Sep 2018
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis
  Lesion Detection and Segmentation
Exploring Uncertainty Measures in Deep Networks for Multiple Sclerosis Lesion Detection and Segmentation
T. Nair
Doina Precup
Douglas L. Arnold
Tal Arbel
UQCV
65
448
0
03 Aug 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Battista Biggio
Fabio Roli
AAML
137
1,409
0
08 Dec 2017
Ensembles of Multiple Models and Architectures for Robust Brain Tumour
  Segmentation
Ensembles of Multiple Models and Architectures for Robust Brain Tumour Segmentation
Konstantinos Kamnitsas
Wenjia Bai
Enzo Ferrante
Jingyu Sun
Matthew Sinclair
...
Martin Rajchl
Matthew C. H. Lee
Bernhard Kainz
Daniel Rueckert
Ben Glocker
3DVAAMLOOD
67
436
0
04 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILMOOD
325
12,151
0
19 Jun 2017
On Calibration of Modern Neural Networks
On Calibration of Modern Neural Networks
Chuan Guo
Geoff Pleiss
Yu Sun
Kilian Q. Weinberger
UQCV
299
5,877
0
14 Jun 2017
Ensemble Sampling
Ensemble Sampling
Xiuyuan Lu
Benjamin Van Roy
152
121
0
20 May 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep
  Ensembles
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles
Balaji Lakshminarayanan
Alexander Pritzel
Charles Blundell
UQCVBDL
850
5,849
0
05 Dec 2016
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for
  Semantic Segmentation
The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation
S. Jégou
M. Drozdzal
David Vazquez
Adriana Romero
Yoshua Bengio
SSeg
217
1,580
0
28 Nov 2016
Delving into Transferable Adversarial Examples and Black-box Attacks
Delving into Transferable Adversarial Examples and Black-box Attacks
Yanpei Liu
Xinyun Chen
Chang-rui Liu
Basel Alomair
AAML
147
1,741
0
08 Nov 2016
Densely Connected Convolutional Networks
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN3DV
895
36,910
0
25 Aug 2016
The Importance of Skip Connections in Biomedical Image Segmentation
The Importance of Skip Connections in Biomedical Image Segmentation
M. Drozdzal
Eugene Vorontsov
Gabriel Chartrand
Samuel Kadoury
C. Pal
MedIm
90
1,048
0
14 Aug 2016
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets,
  Atrous Convolution, and Fully Connected CRFs
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Liang-Chieh Chen
George Papandreou
Iasonas Kokkinos
Kevin Patrick Murphy
Alan Yuille
SSeg
280
18,298
0
02 Jun 2016
Fully Convolutional Networks for Semantic Segmentation
Fully Convolutional Networks for Semantic Segmentation
Evan Shelhamer
Jonathan Long
Trevor Darrell
VOSSSeg
760
37,927
0
20 May 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,641
0
10 Dec 2015
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder
  Architectures for Scene Understanding
Bayesian SegNet: Model Uncertainty in Deep Convolutional Encoder-Decoder Architectures for Scene Understanding
Alex Kendall
Vijay Badrinarayanan
R. Cipolla
UQCVBDL
98
1,066
0
09 Nov 2015
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image
  Segmentation
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Vijay Badrinarayanan
Alex Kendall
R. Cipolla
SSeg
1.1K
15,846
0
02 Nov 2015
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
UQCVBDL
909
9,364
0
06 Jun 2015
Weight Uncertainty in Neural Networks
Weight Uncertainty in Neural Networks
Charles Blundell
Julien Cornebise
Koray Kavukcuoglu
Daan Wierstra
UQCVBDL
196
1,894
0
20 May 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.9K
77,520
0
18 May 2015
Explaining and Harnessing Adversarial Examples
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAMLGAN
284
19,145
0
20 Dec 2014
1