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Organ segmentation in CT volumes is an important pre-processing step in many computer assisted intervention and diagnosis methods.
User-guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability
Paul A. Yushkevich, Joseph Piven, Heather Cody Hazlett, Rachel Gimpel Smith, Sean Ho, James C. Gee, and Guido Gerig · 2006
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Statistics in brief: the importance of sample size in the planning and interpretation of medical research
David Jean Biau, Solen Kernéis, and Raphaël Porcher · 2008
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Efficient inference in fully connected crfs with gaussian edge potentials
Philip Krähenbühl and Vladlen Koltun · 2011
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The cancer imaging archive (tcia): Maintaining and operating a public information repository
Kenneth Clark, Bruce Vendt, Kirk Smith, John Freymann, Justin Kirby, Paul Koppel, Stephen Moore, Stanley Phillips, David Maffitt, Michael Pringle, Lawrence Tarbox, and Fred Prior · 2013
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation
Holger R. Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim Turkbey, and Ronald M. Summers · 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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Data from pancreas-ct. the cancer imaging archive
Holger R. Roth, Amal Farag, Evrim B. Turkbey, Le Lu, Jiamin Liu, and Ronald M. Summers · 2016
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Semi-supervised learning for network-based cardiac mr image segmentation
Wenjia Bai, Ozan Oktay, Matthew Sinclair, Hideaki Suzuki, Martin Rajchl, Giacomo Tarroni, Ben Glocker, Andrew King, Paul M. Matthews, and Daniel Rueckert · 2017
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Efficient multi-scale 3d cnn with fully connected crf for accurate brain lesion segmentation
Konstantinos Kamnitsas, Christian Ledig, Virginia F.J. Newcombe, Joanna P. Simpson, Andrew D. Kane, David K. Menon, Daniel Rueckert, and Ben Glocker · 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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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Anatomically constrained neural networks (acnns): application to cardiac image enhancement and segmentation
Ozan Oktay, Enzo Ferrante, Konstantinos Kamnitsas, Mattias Heinrich, Wenjia Bai, Jose Caballero, Stuart A Cook, Antonio De Marvao, Timothy Dawes, Declan P O‘Regan, et al · 2017
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When null hypothesis significance testing is unsuitable for research: A reassessment
Debes Szucs and John P. A. Ioannidis · 2017
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Fine-tuning convolutional neural networks for biomedical image analysis: Actively and incrementally
Zongwei Zhou, Jae Shin, Lei Zhang, Suryakanth Gurudu, Michael Gotway, and Jianming Liang · 2017
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Domain and geometry agnostic cnns for left atrium segmentation in 3d ultrasound
Markus A Degel, Nassir Navab, and Shadi Albarqouni · 2018
Cited alongside, same era.
Cancer metastasis detection with neural conditional random field
Yi Li and Wei Ping · 2018
Cited alongside, same era.
Semantic segmentation refinement by monte carlo region growing of high confidence detections
Philipe Ambrozio Dias and Henry Medeiros · 2019
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A joint 3d unet-graph neural network-based method for airway segmentation from chest cts
Antonio Garcia-Uceda Juarez, Raghavendra Selvan, Zaigham Saghir, and Marleen de Bruijne · 2019
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We know where we don’t know: 3d bayesian cnns for credible geometric uncertainty
Tyler LaBonte, Carianne Martinez, and Scott Roberts · 2019
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Deep vessel segmentation by learning graphical connectivity
Seung Yeon Shin, Soochahn Lee, Il Dong Yun, and Kyoung Mu Lee · 2019
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Amber L. Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello, Keyvan Farahani, Bram van Ginneken, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M. Summers, Patrick Bilic, Patrick F. Christ, Richard K. G. Do, Marc Gollub, Jennifer Golia-Pernicka, Stephan H. Heckers, William R. Jarnagin, Maureen K. McHugo, Sandy Napel, Eugene Vorontsov, Lena Maier-Hein, and M. Jorge Cardoso · 2019
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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 · 2018
Cited alongside, same era.
Attention u-net: Learning where to look for the pancreas
Ozan Oktay, Jo Schlemper, Loic Le Folgoc, Matthew Lee, Mattias Heinrich, Kazunari Misawa, Kensaku Mori, Steven McDonagh, Nils Y Hammerla, Bernhard Kainz, Ben Glocker, and Daniel Rueckert1 · 2018
Cited alongside, same era.
Towards dense volumetric pancreas segmentation in ct using 3d fully convolutional networks
Holger Roth, Masahiro Oda, Natsuki Shimizu, Hirohisa Oda, Yuichiro Hayashi, Takayuki Kitasaka, Michitaka Fujiwara, Kazunari Misawa, and Kensaku Mori · 2018
Cited alongside, same era.
Extraction of airways using graph neural networks
Raghavendra Selvan, Thomas Kipf, Max Welling, Jesper H. Pedersen, Jens Petersen, and Marleen de Bruijne · 2018
Cited alongside, same era.
Interactive medical image segmentation using deep learning with image-specific fine tuning
Guotai Wang, Wenqi Li, Maria A. Zuluaga, Rosalind Pratt, Premal A. Patel, Michael Aertsen, Tom Doel, Anna L. David, Jan Deprest, Sebastien Ourselin, and Tom Vercauteren · 2018
Cited alongside, same era.
3d semi-supervised learning with uncertainty-aware multi-view co-training
Yingda Xia, Fengze Liu, Dong Yang, Jinzheng Cai, Lequan Yu, Zhuotun Zhu, Daguang Xu, Alan Yuille, and Holger Roth · 2018
Cited alongside, same era.
A 3d coarse-to-fine framework for volumetric medical image segmentation
Zhuotun Zhu, Yingda Xia, Wei Shen, Elliot K. Fishman, and Alan L. Yuille · 2018
Cited alongside, same era.
Later among the works it cites.
Learn to estimate labels uncertainty for quality assurance
Agnieszka Tomczack, Nassir Navab, and Shadi Albarqouni · 2019
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Abdominal multi-organ segmentation with organ-attention networks and statistical fusion
Yan Wang, Yuyin Zhou, Wei Shen, Seyoun Park, Elliot K. Fishman, and Alan L. Yuille · 2019
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Integrating 3d geometry of organ for improving medical image segmentation
Jiawen Yao, Jinzheng Cai, Dong Yang, Daguang Xu, and Junzhou Huang · 2019
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Uncertainty-aware self-ensembling model for semi-supervised 3d left atrium segmentation
Lequan Yu, Shujun Wang, Xiaomeng Li, Chi-Wing Fu, and Pheng-Ann Heng · 2019
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Prior-aware neural network for partially-supervised multi-organ segmentation
Yuyin Zhou, Zhe Li, Song Bai, Chong Wang, Xinlei Chen, Mei Han, Elliot K. Fishman, and Alan L. Yuille · 2019
Later among the works it cites.
Uncertainty-based graph convolutional networks for organ segmentation refinement
Roger D. Soberanis-Mukul, Nassir Navab, and Shadi Albarqouni · 2020
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