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Quantifying and Leveraging Classification Uncertainty for Chest
  Radiograph Assessment

Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment

18 June 2019
Florin-Cristian Ghesu
Bogdan Georgescu
Eli Gibson
Sebastian Gündel
Mannudeep K. Kalra
Ramandeep Singh
S. Digumarthy
Sasa Grbic
Dorin Comaniciu
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Quantifying and Leveraging Classification Uncertainty for Chest Radiograph Assessment"

16 / 16 papers shown
Title
Trustworthy clinical AI solutions: a unified review of uncertainty
  quantification in deep learning models for medical image analysis
Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis
Benjamin Lambert
Florence Forbes
A. Tucholka
Senan Doyle
Harmonie Dehaene
M. Dojat
110
90
0
05 Oct 2022
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in
  Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking
  Results
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta
Angelos Filos
Ujjwal Baid
C. Sako
Richard McKinley
...
Christos Davatzikos
Bjoern Menze
Spyridon Bakas
Y. Gal
Tal Arbel
UQCV
110
49
0
19 Dec 2021
A Survey of Uncertainty in Deep Neural Networks
A Survey of Uncertainty in Deep Neural Networks
J. Gawlikowski
Cedrique Rovile Njieutcheu Tassi
Mohsin Ali
Jongseo Lee
Matthias Humt
...
R. Roscher
Muhammad Shahzad
Wen Yang
R. Bamler
Xiaoxiang Zhu
BDLUQCVOOD
242
1,177
0
07 Jul 2021
Robust Classification from Noisy Labels: Integrating Additional
  Knowledge for Chest Radiography Abnormality Assessment
Robust Classification from Noisy Labels: Integrating Additional Knowledge for Chest Radiography Abnormality Assessment
Sebastian Gündel
A. Setio
Florin-Cristian Ghesu
Sasa Grbic
Bogdan Georgescu
Andreas Maier
Dorin Comaniciu
NoLa
70
28
0
12 Apr 2021
Deep Learning for Chest X-ray Analysis: A Survey
Deep Learning for Chest X-ray Analysis: A Survey
Ecem Sogancioglu
E. Çallı
Bram van Ginneken
K. G. V. Leeuwen
K. Murphy
LM&MA
124
329
0
15 Mar 2021
Improving Medical Image Classification with Label Noise Using
  Dual-uncertainty Estimation
Improving Medical Image Classification with Label Noise Using Dual-uncertainty Estimation
Lie Ju
Xin Eric Wang
Lin Wang
Dwarikanath Mahapatra
Xin Zhao
Mehrtash Harandi
Tom Drummond
Tongliang Liu
Z. Ge
NoLaOOD
97
23
0
28 Feb 2021
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted
  Labels
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels
Jintai Chen
Hongyun Yu
Ruiwei Feng
Danny Chen
Jian Wu
48
13
0
09 Feb 2021
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
125
72
0
07 Jan 2021
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
BDLUQCV
360
1,947
0
12 Nov 2020
A review of deep learning in medical imaging: Imaging traits, technology
  trends, case studies with progress highlights, and future promises
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S. Kevin Zhou
H. Greenspan
Christos Davatzikos
James S. Duncan
Bram van Ginneken
A. Madabhushi
Jerry L. Prince
Daniel Rueckert
Ronald M. Summers
215
649
0
02 Aug 2020
Curriculum learning for improved femur fracture classification:
  scheduling data with prior knowledge and uncertainty
Curriculum learning for improved femur fracture classification: scheduling data with prior knowledge and uncertainty
Amelia Jiménez-Sánchez
Diana Mateus
S. Kirchhoff
C. Kirchhoff
P. Biberthaler
Nassir Navab
M. A. G. Ballester
Gemma Piella
39
19
0
31 Jul 2020
Quantifying and Leveraging Predictive Uncertainty for Medical Image
  Assessment
Quantifying and Leveraging Predictive Uncertainty for Medical Image Assessment
Florin-Cristian Ghesu
Bogdan Georgescu
Awais Mansoor
Y. Yoo
Eli Gibson
...
Ramandeep Singh
S. Digumarthy
Mannudeep K. Kalra
Sasa Grbic
Dorin Comaniciu
UQCVEDL
63
55
0
08 Jul 2020
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale
  Multi-phase CT Data via Deep Dynamic Texture Learning
Harvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning
Yuankai Huo
Jinzheng Cai
Chi-Tung Cheng
Ashwin Raju
K. Yan
Bennett A. Landman
Jing Xiao
Le Lu
Chien-Hung Liao
Adam P. Harrison
MedIm
67
11
0
28 Jun 2020
Deep Mining External Imperfect Data for Chest X-ray Disease Screening
Deep Mining External Imperfect Data for Chest X-ray Disease Screening
Luyang Luo
Lequan Yu
Hao Chen
Quande Liu
Xi Wang
Jiaqi Xu
Pheng-Ann Heng
OOD
89
79
0
06 Jun 2020
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT
  Scans by Augmenting with Adversarial Attacks
No Surprises: Training Robust Lung Nodule Detection for Low-Dose CT Scans by Augmenting with Adversarial Attacks
Siqi Liu
A. Setio
Florin-Cristian Ghesu
Eli Gibson
Sasa Grbic
Bogdan Georgescu
Dorin Comaniciu
AAMLOOD
117
40
0
08 Mar 2020
Model-Based and Data-Driven Strategies in Medical Image Computing
Model-Based and Data-Driven Strategies in Medical Image Computing
Daniel Rueckert
Julia A. Schnabel
OODMedImAI4CE
62
50
0
23 Sep 2019
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