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The performance on deep learning is significantly affected by volume of training data.
Lung image database consortium: developing a resource for the medical imaging research community
Samuel G Armato III, Geoffrey McLennan, Michael F McNitt-Gray, Charles R Meyer, David Yankelevitz, Denise R Aberle, Claudia I Henschke, Eric A Hoffman, Ella A Kazerooni, Heber MacMahon, et al · 2004
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The difficulty of training deep architectures and the effect of unsupervised pre-training
Dumitru Erhan, Pierre-Antoine Manzagol, Yoshua Bengio, Samy Bengio, and Pascal Vincent · 2009
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Domain adaptation from multiple sources via auxiliary classifiers
Lixin Duan, Ivor W Tsang, Dong Xu, and Tat-Seng Chua · 2009
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The PASCAL visual object classes (VOC) challenge
Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman · 2010
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A survey on transfer learning
Sinno Jialin Pan and Qiang Yang · 2010
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The lung image database consortium (LIDC) and image database resource initiative (IDRI): a completed reference database of lung nodules on CT scans
Samuel G Armato III, Geoffrey McLennan, Luc Bidaut, Michael F McNitt-Gray, Charles R Meyer, Anthony P Reeves, Binsheng Zhao, Denise R Aberle, Claudia I Henschke, Eric A Hoffman, et al · 2011
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Discovering latent domains for multisource domain adaptation
Judy Hoffman, Brian Kulis, Trevor Darrell, and Kate Saenko · 2012
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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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, et al · 2013
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Beyond thick versus thin: mapping cranial vault thickness patterns in recent homo sapiens
Hannah Eyre Marsh · 2013
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Microsoft COCO: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
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Food image recognition using deep convolutional network with pre-training and fine-tuning
Keiji Yanai and Yoshiyuki Kawano · 2015
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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 · 2015
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Benchmark for algorithms segmenting the left atrium from 3d ct and mri datasets
Catalina Tobon-Gomez, Arjan J Geers, Jochen Peters, Jürgen Weese, Karen Pinto, Rashed Karim, Mohammed Ammar, Abdelaziz Daoudi, Jan Margeta, Zulma Sandoval, et al · 2015
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Texture feature analysis for computer-aided diagnosis on pulmonary nodules
Fangfang Han, Huafeng Wang, Guopeng Zhang, Hao Han, Bowen Song, Lihong Li, William Moore, Hongbing Lu, Hong Zhao, and Zhengrong Liang · 2015
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Understanding the mechanisms of deep transfer learning for medical images
Hariharan Ravishankar, Prasad Sudhakar, Rahul Venkataramani, Sheshadri Thiruvenkadam, Pavan Annangi, Narayanan Babu, and Vivek Vaidya · 2016
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Convolutional neural networks for medical image analysis: Full training or fine tuning?
Nima Tajbakhsh, Jae Y Shin, Suryakanth R Gurudu, R Todd Hurst, Christopher B Kendall, Michael B Gotway, and Jianming Liang · 2016
Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015
Patrik F Raudaschl, Paolo Zaffino, Gregory C Sharp, Maria Francesca Spadea, Antong Chen, Benoit M Dawant, Thomas Albrecht, Tobias Gass, Christoph Langguth, Marcel Lüthi, et al · 2017
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H-DenseUNet: Hybrid densely connected unet for liver and tumor segmentation from ct volumes
X. Li, H. Chen, X. Qi, Q. Dou, C. W. Fu, and P. A. Heng · 2017
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Recurrent saliency transformation network: Incorporating multi-stage visual cues for small organ segmentation
Qihang Yu, Lingxi Xie, Yan Wang, Yuyin Zhou, Elliot K Fishman, and Alan L Yuille · 2018
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Rethinking ImageNet Pre-training
Kaiming He, Ross Girshick, and Piotr Dollár · 2018
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Cloud-based evaluation of anatomical structure segmentation and landmark detection algorithms: Visceral anatomy benchmarks
Oscar Jimenez-del Toro, Henning Müller, Markus Krenn, Katharina Gruenberg, Abdel Aziz Taha, Marianne Winterstein, Ivan Eggel, Antonio Foncubierta-Rodríguez, Orcun Goksel, András Jakab, et al · 2016
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Automatic segmentation of left ventricular myocardium by deep convolutional and de-convolutional neural networks
XL Yang, L Gobeawan, SY Yeo, WT Tang, ZZ Wu, and Y Su · 2016
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V-Net: Fully convolutional neural networks for volumetric medical image segmentation
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016
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3D U-Net: learning dense volumetric segmentation from sparse annotation
Özgün Çiçek, Ahmed Abdulkadir, Soeren S Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016
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Learning multi-domain convolutional neural networks for visual tracking
Hyeonseob Nam and Bohyung Han · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Identity mappings in deep residual networks
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
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3D deep learning from ct scans predicts tumor invasiveness of subcentimeter pulmonary adenocarcinomas
Wei Zhao, Jiancheng Yang, Yingli Sun, Cheng Li, Weilan Wu, Liang Jin, Zhiming Yang, Bingbing Ni, Pan Gao, Peijun Wang, et al · 2018
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Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet
Kensho Hara, Hirokatsu Kataoka, and Yutaka Satoh · 2018
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Fully automatic left atrium segmentation from late gadolinium enhanced magnetic resonance imaging using a dual fully convolutional neural network
Zhaohan Xiong, Vadim V Fedorov, Xiaohang Fu, Elizabeth Cheng, Rob Macleod, and Jichao Zhao · 2018
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DenseASPP for semantic segmentation in street scenes
Maoke Yang, Kun Yu, Chi Zhang, Zhiwei Li, and Kuiyuan Yang · 2018
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Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs
Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2018
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Can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet?
Kensho Hara, Hirokatsu Kataoka, and Yutaka Satoh · 2018
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3D anisotropic hybrid network: Transferring convolutional features from 2D images to 3D anisotropic volumes
Siqi Liu, Daguang Xu, S. Kevin Zhou, Olivier Pauly, Sasa Grbic, Thomas Mertelmeier, Julia Wicklein, Anna Jerebko, Weidong Cai, and Dorin Comaniciu · 2018
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Evaluation of algorithms for multi-modality whole heart segmentation: An open-access grand challenge
Xiahai Zhuang, Lei Li, Christian Payer, Darko Stern, Martin Urschler, Mattias P Heinrich, Julien Oster, Chunliang Wang, Orjan Smedby, Cheng Bian, et al · 2019
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