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Diffusion models have shown impressive performance for generative modelling of images.
The multimodal brain tumor image segmentation benchmark (BRATS)
Bjoern H Menze, Andras Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, et al · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani · 2016
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
Vijay Badrinarayanan, Alex Kendall, and Roberto Cipolla · 2017
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Advancing the cancer genome atlas glioma MRI collections with expert segmentation labels and radiomic features
Spyridon Bakas, Hamed Akbari, Aristeidis Sotiras, Michel Bilello, Martin Rozycki, Justin S Kirby, John B Freymann, Keyvan Farahani, and Christos Davatzikos · 2017
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What uncertainties do we need in bayesian deep learning for computer vision?
Alex Kendall and Yarin Gal · 2017
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Spyridon Bakas, Mauricio Reyes, Andras Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, et al · 2018
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Leveraging uncertainty estimates for predicting segmentation quality
Terrance DeVries and Graham W Taylor · 2018
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Whole heart segmentation from ct images using 3d u-net architecture
Marija Habijan, Hrvoje Leventić, Irena Galić, and Danilo Babin · 2019
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Assessing reliability and challenges of uncertainty estimations for medical image segmentation
Alain Jungo and Mauricio Reyes · 2019
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A dense u-net architecture for multiple sclerosis lesion segmentation
Amish Kumar, Oduri Narayana Murthy, Palash Ghosal, Amritendu Mukherjee, Debashis Nandi, et al · 2019
Cited alongside, same era.
On the validity of bayesian neural networks for uncertainty estimation
John Mitros and Brian Mac Namee · 2019
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Aleatoric uncertainty estimation with test-time augmentation for medical image segmentation with convolutional neural networks
Guotai Wang, Wenqi Li, Michael Aertsen, Jan Deprest, Sébastien Ourselin, and Tom Vercauteren · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
Moloud Abdar, Farhad Pourpanah, Sadiq Hussain, Dana Rezazadegan, Li Liu, Mohammad Ghavamzadeh, Paul Fieguth, Xiaochun Cao, Abbas Khosravi, U Rajendra Acharya, et al · 2021
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Segdiff: Image segmentation with diffusion probabilistic models
Tomer Amit, Eliya Nachmani, Tal Shaharbany, and Lior Wolf · 2021
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Label-efficient semantic segmentation with diffusion models
Dmitry Baranchuk, Ivan Rubachev, Andrey Voynov, Valentin Khrulkov, and Artem Babenko · 2021
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Ilvr: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon · 2021
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Raghav Mehta, Angelos Filos, Yarin Gal, and Tal Arbel · 2020
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Exploring uncertainty measures in deep networks for multiple sclerosis lesion detection and segmentation
Tanya Nair, Doina Precup, Douglas L Arnold, and Tal Arbel · 2020
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Deep learning approaches to biomedical image segmentation
Intisar Rizwan I Haque and Jeremiah Neubert · 2020
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Uncertainty quantification using variational inference for biomedical image segmentation
Abhinav Sagar · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Segmentation of lung nodules using improved 3d-unet neural network
Zhitao Xiao, Bowen Liu, Lei Geng, Fang Zhang, and Yanbei Liu · 2020
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Alex Kendall, Vijay Badrinarayanan, and Roberto Cipolla
Cited in the paper.
Alex Kendall, Vijay Badrinarayanan, and Roberto Cipolla
Cited in the paper.
Prafulla Dhariwal and Alex Nichol · 2021
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nnu-net: a self-configuring method for deep learning-based biomedical image segmentation
Fabian Isensee, Paul F Jaeger, Simon AA Kohl, Jens Petersen, and Klaus H Maier-Hein · 2021
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Improved denoising diffusion probabilistic models
Alex Nichol and Prafulla Dhariwal · 2021
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Palette: Image-to-image diffusion models
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Unit-ddpm: Unpaired image translation with denoising diffusion probabilistic models
Hiroshi Sasaki, Chris G Willcocks, and Toby P Breckon · 2021
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3d deep neural network segmentation of intracerebral hemorrhage: Development and validation for clinical trials
Matthew F Sharrock, W Andrew Mould, Hasan Ali, Meghan Hildreth, Issam A Awad, Daniel F Hanley, and John Muschelli · 2021
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