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. 1807.07356
  4. Cited By
Aleatoric uncertainty estimation with test-time augmentation for medical
  image segmentation with convolutional neural networks

Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks

19 July 2018
Guotai Wang
Wenqi Li
Michael Aertsen
Jan Deprest
Sebastien Ourselin
Tom Kamiel Magda Vercauteren
    UQCV
    MedIm
    OOD
ArXivPDFHTML

Papers citing "Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks"

44 / 244 papers shown
Title
Diminishing Uncertainty within the Training Pool: Active Learning for
  Medical Image Segmentation
Diminishing Uncertainty within the Training Pool: Active Learning for Medical Image Segmentation
V. Nath
Dong Yang
Bennett A. Landman
Daguang Xu
H. Roth
35
68
0
07 Jan 2021
Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation:
  A Benchmark Study
Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study
Matthew Ng
F. Guo
L. Biswas
S. Petersen
Stefan K. Piechnik
S. Neubauer
G. Wright
UQCV
17
32
0
31 Dec 2020
SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with
  Uncertainty Estimation and Explainability
SkiNet: A Deep Learning Solution for Skin Lesion Diagnosis with Uncertainty Estimation and Explainability
R. Singh
R. Gorantla
Sai Giridhar Allada
N. Pratap
19
3
0
30 Dec 2020
Exploring Instance-Level Uncertainty for Medical Detection
Exploring Instance-Level Uncertainty for Medical Detection
Jiawei Yang
Yuan Liang
Yao Zhang
Weinan Song
Kun Wang
Lei He
UQCV
21
5
0
23 Dec 2020
Leaf Segmentation and Counting with Deep Learning: on Model Certainty,
  Test-Time Augmentation, Trade-Offs
Leaf Segmentation and Counting with Deep Learning: on Model Certainty, Test-Time Augmentation, Trade-Offs
D. Gomes
Lihong Zheng
11
6
0
21 Dec 2020
Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal
  Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
Efficient Semi-Supervised Gross Target Volume of Nasopharyngeal Carcinoma Segmentation via Uncertainty Rectified Pyramid Consistency
Xiangde Luo
Wenjun Liao
Jieneng Chen
Tao Song
Yinan Chen
Shichuan Zhang
N. Chen
Guotai Wang
Shaoting Zhang
23
218
0
13 Dec 2020
Temporal Representation Learning on Monocular Videos for 3D Human Pose
  Estimation
Temporal Representation Learning on Monocular Videos for 3D Human Pose Estimation
S. Honari
Victor Constantin
Helge Rhodin
Mathieu Salzmann
Pascal Fua
3DH
34
10
0
02 Dec 2020
Better Aggregation in Test-Time Augmentation
Better Aggregation in Test-Time Augmentation
Divya Shanmugam
Davis W. Blalock
Guha Balakrishnan
John Guttag
ViT
25
145
0
23 Nov 2020
A Review of Uncertainty Quantification in Deep Learning: Techniques,
  Applications and Challenges
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges
Moloud Abdar
Farhad Pourpanah
Sadiq Hussain
Dana Rezazadegan
Li Liu
...
Xiaochun Cao
Abbas Khosravi
U. Acharya
V. Makarenkov
S. Nahavandi
BDL
UQCV
56
1,883
0
12 Nov 2020
Uncertainty Estimation in Medical Image Localization: Towards Robust
  Anterior Thalamus Targeting for Deep Brain Stimulation
Uncertainty Estimation in Medical Image Localization: Towards Robust Anterior Thalamus Targeting for Deep Brain Stimulation
Han Liu
C. Cui
Dario J. Englot
Benoit M. Dawant
16
2
0
03 Nov 2020
Generalized Wasserstein Dice Score, Distributionally Robust Deep
  Learning, and Ranger for brain tumor segmentation: BraTS 2020 challenge
Generalized Wasserstein Dice Score, Distributionally Robust Deep Learning, and Ranger for brain tumor segmentation: BraTS 2020 challenge
Lucas Fidon
Sebastien Ourselin
Tom Kamiel Magda Vercauteren
OOD
MedIm
24
41
0
03 Nov 2020
Learning Loss for Test-Time Augmentation
Learning Loss for Test-Time Augmentation
Ildoo Kim
Younghoon Kim
Sungwoong Kim
OOD
26
90
0
22 Oct 2020
ivadomed: A Medical Imaging Deep Learning Toolbox
ivadomed: A Medical Imaging Deep Learning Toolbox
C. Gros
A. Lemay
Olivier Vincent
Lucas Rouhier
Anthime Bucquet
Joseph Paul Cohen
Julien Cohen-Adad
LM&MA
MedIm
27
15
0
20 Oct 2020
The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using
  ResNet34 as a Backbone for U-Net
The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using ResNet34 as a Backbone for U-Net
Ayat Abedalla
Malak Abdullah
M. Al-Ayyoub
E. Benkhelifa
14
13
0
06 Sep 2020
Integrating uncertainty in deep neural networks for MRI based stroke
  analysis
Integrating uncertainty in deep neural networks for MRI based stroke analysis
L. Herzog
Elvis Murina
Oliver Durr
S. Wegener
Beate Sick
10
51
0
13 Aug 2020
Uncertainty Quantification using Variational Inference for Biomedical
  Image Segmentation
Uncertainty Quantification using Variational Inference for Biomedical Image Segmentation
Abhinav Sagar
UQCV
13
16
0
12 Aug 2020
Real-time CNN-based Segmentation Architecture for Ball Detection in a
  Single View Setup
Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup
Gabriel Van Zandycke
Christophe De Vleeschouwer
13
13
0
23 Jul 2020
Exploiting Uncertainties from Ensemble Learners to Improve
  Decision-Making in Healthcare AI
Exploiting Uncertainties from Ensemble Learners to Improve Decision-Making in Healthcare AI
Yingshui Tan
Baihong Jin
Xiangyu Yue
Yuxin Chen
Alberto L. Sangiovanni-Vincentelli
10
7
0
12 Jul 2020
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions
  in Medical Domain
Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
Takahiro Mimori
Keiko Sasada
H. Matsui
Issei Sato
UQCV
17
6
0
03 Jul 2020
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain
  Segmentation from Stacks of MRI Slices
Uncertainty-Guided Efficient Interactive Refinement of Fetal Brain Segmentation from Stacks of MRI Slices
Guotai Wang
Michael Aertsen
Jan Deprest
Sebastien Ourselin
Tom Kamiel Magda Vercauteren
Shaoting Zhang
31
34
0
02 Jul 2020
Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse
  Surgical Instrument Usage for Context-aware Assistance
Rethinking Anticipation Tasks: Uncertainty-aware Anticipation of Sparse Surgical Instrument Usage for Context-aware Assistance
Dominik Rivoir
S. Bodenstedt
Isabel Funke
F. Bechtolsheim
Marius Distler
Jürgen Weitz
Stefanie Speidel
24
24
0
01 Jul 2020
Stochastic Segmentation Networks: Modelling Spatially Correlated
  Aleatoric Uncertainty
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
Miguel A. B. Monteiro
Loic Le Folgoc
Daniel Coelho De Castro
Nick Pawlowski
Bernardo Marques
Konstantinos Kamnitsas
Mark van der Wilk
Ben Glocker
UQCV
BDL
28
113
0
10 Jun 2020
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced
  Learning from Noisy Labels with Suggestive Annotation
Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation
Jingyang Zhang
Guotai Wang
Hongzhi Xie
Shuyang Zhang
Ning Huang
Shaoting Zhang
Lixu Gu
35
41
0
27 May 2020
Uncertainty Estimation in Deep 2D Echocardiography Segmentation
Uncertainty Estimation in Deep 2D Echocardiography Segmentation
Lavsen Dahal
Aayush Kafle
Bishesh Khanal
UQCV
17
10
0
19 May 2020
Improving Calibration and Out-of-Distribution Detection in Medical Image
  Segmentation with Convolutional Neural Networks
Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural Networks
Davood Karimi
Ali Gholipour
OOD
28
9
0
12 Apr 2020
$F$, $B$, Alpha Matting
FFF, BBB, Alpha Matting
Marco Forte
François Pitié
25
84
0
17 Mar 2020
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
147
427
0
09 Mar 2020
Greedy Policy Search: A Simple Baseline for Learnable Test-Time
  Augmentation
Greedy Policy Search: A Simple Baseline for Learnable Test-Time Augmentation
Dmitry Molchanov
Alexander Lyzhov
Yuliya Molchanova
Arsenii Ashukha
Dmitry Vetrov
TPM
27
84
0
21 Feb 2020
A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image
  Quality
A Heteroscedastic Uncertainty Model for Decoupling Sources of MRI Image Quality
Richard Shaw
Carole H. Sudre
Sebastien Ourselin
M. Jorge Cardoso
UQCV
22
13
0
31 Jan 2020
Parameters Estimation for the Cosmic Microwave Background with Bayesian
  Neural Networks
Parameters Estimation for the Cosmic Microwave Background with Bayesian Neural Networks
Héctor J. Hortúa
Riccardo Volpi
D. Marinelli
Luigi Malagò
BDL
11
22
0
19 Nov 2019
A Survey on Active Learning and Human-in-the-Loop Deep Learning for
  Medical Image Analysis
A Survey on Active Learning and Human-in-the-Loop Deep Learning for Medical Image Analysis
Samuel Budd
E. C. Robinson
Bernhard Kainz
LM&MA
6
469
0
07 Oct 2019
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity
  as a Surrogate
Training-Free Uncertainty Estimation for Dense Regression: Sensitivity as a Surrogate
Lu Mi
Hao Wang
Yonglong Tian
Hao He
Nir Shavit
UQCV
21
30
0
28 Sep 2019
Swapped Face Detection using Deep Learning and Subjective Assessment
Swapped Face Detection using Deep Learning and Subjective Assessment
Xinyi Ding
Zohreh Raziei
Eric C. Larson
E. Olinick
P. Krueger
Michael Hahsler
PICV
CVBM
34
65
0
10 Sep 2019
As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging
As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging
Zach Eaton-Rosen
Thomas Varsavsky
Sebastien Ourselin
M. Jorge Cardoso
UQCV
23
12
0
25 Jul 2019
Bayesian Modelling in Practice: Using Uncertainty to Improve
  Trustworthiness in Medical Applications
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications
David Ruhe
Giovanni Cina
Michele Tonutti
D. D. Bruin
Paul Elbers
OOD
12
13
0
20 Jun 2019
Task Decomposition and Synchronization for Semantic Biomedical Image
  Segmentation
Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation
Xuhua Ren
Lichi Zhang
Sahar Ahmad
Dong Nie
Fan Yang
L. Xiang
Qian Wang
Dinggang Shen
19
26
0
21 May 2019
Gaze Training by Modulated Dropout Improves Imitation Learning
Gaze Training by Modulated Dropout Improves Imitation Learning
Yuying Chen
Congcong Liu
L. Tai
Ming Liu
Bertram E. Shi
17
16
0
17 Apr 2019
CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
CaseNet: Content-Adaptive Scale Interaction Networks for Scene Parsing
Xin Jin
Cuiling Lan
Wenjun Zeng
Zhizheng Zhang
Zhibo Chen
21
7
0
17 Apr 2019
Few-shot brain segmentation from weakly labeled data with deep
  heteroscedastic multi-task networks
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks
Richard McKinley
Michael Rebsamen
Raphael Meier
M. Reyes
C. Rummel
Roland Wiest
14
13
0
04 Apr 2019
Accuracy, Uncertainty, and Adaptability of Automatic Myocardial ASL
  Segmentation using Deep CNN
Accuracy, Uncertainty, and Adaptability of Automatic Myocardial ASL Segmentation using Deep CNN
H. P. Do
Yi Guo
A. Yoon
K. Nayak
23
22
0
10 Dec 2018
MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine
  Collaboration in Breast Cancer Diagnosis
MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis
Nesreen Ahmed
Theodore L. Willke
M. Schaar
22
32
0
30 Oct 2018
Automatic Brain Tumor Segmentation using Convolutional Neural Networks
  with Test-Time Augmentation
Automatic Brain Tumor Segmentation using Convolutional Neural Networks with Test-Time Augmentation
Guotai Wang
Wenqi Li
Sebastien Ourselin
Tom Kamiel Magda Vercauteren
19
151
0
18 Oct 2018
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
5,683
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
287
9,156
0
06 Jun 2015
Previous
12345