U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for
photoreceptor layer segmentation in pathological OCT scans

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U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans

23 January 2019

Philipp Seeböck

Hrvoje Bogunović

Bianca S. Gerendas

U. Schmidt-Erfurth

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Papers citing "U2-Net: A Bayesian U-Net model with epistemic uncertainty feedback for photoreceptor layer segmentation in pathological OCT scans"

13 / 13 papers shown

Title
Bayesian Deep Learning Approaches for Uncertainty-Aware Retinal OCT Image Segmentation for Multiple Sclerosis Samuel T. M. Ball UQCV BDL 271 0 0 17 May 2025
Inter-Rater Uncertainty Quantification in Medical Image Segmentation via Rater-Specific Bayesian Neural Networks Qingqiao Hu Hao Wang Jing Luo Yuan Luo Z. Zhangg Jan S. Kirschke Benedikt Wiestler Bjoern Menze Jianguo Zhang Hongwei Bran Li UQCV 136 2 0 28 Jun 2023
Medical Image Segmentation Review: The success of U-NetIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Reza Azad Ehsan Khodapanah Aghdam Amelie Rauland Yiwei Jia Atlas Haddadi Avval Afshin Bozorgpour Sanaz Karimijafarbigloo Joseph Paul Cohen Ehsan Adeli Dorit Merhof SSeg 196 539 0 27 Nov 2022
Segmentation of Bruch's Membrane in retinal OCT with AMD using anatomical priors and uncertainty quantificationIEEE journal of biomedical and health informatics (IEEE JBHI), 2022 Botond Fazekas Dmitrii Lachinov Guilherme Aresta Julia Mai U. Schmidt-Erfurth Hrvoje Bogunović 94 20 0 26 Oct 2022
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 194 123 0 05 Oct 2022
Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust Benjamin Lambert Florence Forbes Senan Doyle A. Tucholka M. Dojat UQCV MedIm 123 7 0 22 Sep 2022
Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image SegmentationInternational Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2022 Azade Farshad Yousef Yeganeh Peter L. Gehlbach Nassir Navab 122 42 0 15 Apr 2022
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class SegmentationMachine Learning for Biomedical Imaging (MLBI), 2021 Robin Camarasa D. Bos J. Hendrikse P. Nederkoorn D. Epidemiology D. Neurology Department of Computer Science UQCV 139 12 0 22 Sep 2021
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and ChallengesInformation Fusion (Inf. Fusion), 2020 Moloud Abdar Farhad Pourpanah Sadiq Hussain Dana Rezazadegan Tianpeng Liu ... Xiaochun Cao Abbas Khosravi U. Acharya V. Makarenkov S. Nahavandi BDL UQCV 722 2,189 0 12 Nov 2020
U-Net and its variants for medical image segmentation: theory and applicationsIEEE Access (IEEE Access), 2020 N. Siddique Sidike Paheding Colin P. Elkin Vijay Devabhaktuni SSeg 233 1,320 0 02 Nov 2020
An amplified-target loss approach for photoreceptor layer segmentation in pathological OCT scans J. Orlando Anna Breger Hrvoje Bogunović Sophie Riedl Bianca S. Gerendas Martin Ehler U. Schmidt-Erfurth MedIm 108 4 0 02 Aug 2019
Bayesian Modelling in Practice: Using Uncertainty to Improve Trustworthiness in Medical Applications David Ruhe Giovanni Cina Michele Tonutti D. D. Bruin Paul Elbers OOD 98 14 0 20 Jun 2019
Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCTIEEE Transactions on Medical Imaging (TMI), 2019 Philipp Seeböck J. Orlando T. Schlegl S. Waldstein Hrvoje Bogunović S. Klimscha Georg Langs U. Schmidt-Erfurth UQCV 181 143 0 29 May 2019