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Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly
  Detection in Retinal OCT

Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT

29 May 2019
Philipp Seeböck
J. Orlando
T. Schlegl
S. Waldstein
Hrvoje Bogunović
S. Klimscha
Georg Langs
U. Schmidt-Erfurth
    UQCV
ArXiv (abs)PDFHTML

Papers citing "Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT"

20 / 20 papers shown
Title
Bayesian Deep Learning Approaches for Uncertainty-Aware Retinal OCT Image Segmentation for Multiple Sclerosis
Bayesian Deep Learning Approaches for Uncertainty-Aware Retinal OCT Image Segmentation for Multiple Sclerosis
Samuel T. M. Ball
UQCVBDL
192
0
0
17 May 2025
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
262
1
0
25 Nov 2024
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for
  photoreceptor layer segmentation in pathological OCT scans
U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans
J. Orlando
Philipp Seeböck
Hrvoje Bogunović
S. Klimscha
C. Grechenig
S. Waldstein
Bianca S. Gerendas
U. Schmidt-Erfurth
UQCV
38
56
0
23 Jan 2019
Unsupervised Identification of Disease Marker Candidates in Retinal OCT
  Imaging Data
Unsupervised Identification of Disease Marker Candidates in Retinal OCT Imaging Data
Philipp Seeböck
S. Waldstein
S. Klimscha
Hrvoje Bogunović
T. Schlegl
Bianca S. Gerendas
R. Donner
U. Schmidt-Erfurth
Georg Langs
56
81
0
31 Oct 2018
Joint Segmentation and Uncertainty Visualization of Retinal Layers in
  Optical Coherence Tomography Images using Bayesian Deep Learning
Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning
S. Sedai
B. Antony
Dwarikanath Mahapatra
R. Garnavi
UQCV
59
62
0
12 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
60
447
0
03 Aug 2018
Towards a glaucoma risk index based on simulated hemodynamics from
  fundus images
Towards a glaucoma risk index based on simulated hemodynamics from fundus images
J. Orlando
J. Barbosa-Breda
K. V. Keer
Matthew B. Blaschko
P. Blanco
C. Bulant
88
80
0
25 May 2018
Fully Automated Segmentation of Hyperreflective Foci in Optical
  Coherence Tomography Images
Fully Automated Segmentation of Hyperreflective Foci in Optical Coherence Tomography Images
T. Schlegl
Hrvoje Bogunović
S. Klimscha
Philipp Seeböck
A. Sadeghipour
Bianca S. Gerendas
S. Waldstein
Georg Langs
U. Schmidt-Erfurth
52
29
0
08 May 2018
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep
  Learning
CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning
Pranav Rajpurkar
Jeremy Irvin
Kaylie Zhu
Brandon Yang
Hershel Mehta
...
Aarti Bagul
C. Langlotz
K. Shpanskaya
M. Lungren
A. Ng
LM&MA
83
2,709
0
14 Nov 2017
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs
  using Deep Learning
Predicting Cardiovascular Risk Factors from Retinal Fundus Photographs using Deep Learning
Ryan Poplin
A. Varadarajan
Katy Blumer
Yun-Hui Liu
M. McConnell
G. Corrado
L. Peng
D. Webster
MedIm
59
1,338
0
31 Aug 2017
Unsupervised Anomaly Detection with Generative Adversarial Networks to
  Guide Marker Discovery
Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery
T. Schlegl
Philipp Seeböck
S. Waldstein
U. Schmidt-Erfurth
Georg Langs
MedImGAN
108
2,231
0
17 Mar 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer
  Vision?
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?
Alex Kendall
Y. Gal
BDLOODUDUQCVPER
359
4,718
0
15 Mar 2017
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
678
10,796
0
19 Feb 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples
  in Neural Networks
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks
Dan Hendrycks
Kevin Gimpel
UQCV
166
3,468
0
07 Oct 2016
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
89
1,065
0
09 Nov 2015
Bayesian Convolutional Neural Networks with Bernoulli Approximate
  Variational Inference
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
Y. Gal
Zoubin Ghahramani
UQCVBDL
263
751
0
06 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation
U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger
Philipp Fischer
Thomas Brox
SSeg3DV
1.8K
77,341
0
18 May 2015
Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe
Christian Szegedy
OOD
463
43,328
0
11 Feb 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
326
18,647
0
06 Feb 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.9K
150,260
0
22 Dec 2014
1