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Large-scale models pre-trained on large-scale datasets have profoundly advanced the development of deep learning.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
Bennett Landman, Zhoubing Xu, J Igelsias, Martin Styner, T Langerak, and Arno Klein · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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The importance of skip connections in biomedical image segmentation
Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand, Samuel Kadoury, and Chris Pal · 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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V-net: Fully convolutional neural networks for volumetric medical image segmentation
Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016
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Sergey Zagoruyko and Nikos Komodakis · 2016
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Revisiting unreasonable effectiveness of data in deep learning era
Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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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, et al · 2018
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Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc Le · 2019
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Unet++: Redesigning skip connections to exploit multiscale features in image segmentation
Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh, and Jianming Liang · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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The state of the art in kidney and kidney tumor segmentation in contrast-enhanced ct imaging: Results of the kits19 challenge
Nicholas Heller, Fabian Isensee, Klaus H Maier-Hein, Xiaoshuai Hou, Chunmei Xie, Fengyi Li, Yang Nan, Guangrui Mu, Zhiyong Lin, Miofei Han, et al · 2020
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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 2020
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Segthor: Segmentation of thoracic organs at risk in ct images
Zoé Lambert, Caroline Petitjean, Bernard Dubray, and Su Kuan · 2020
Cited alongside, same era.
Ct-org, a new dataset for multiple organ segmentation in computed tomography
Blaine Rister, Darvin Yi, Kaushik Shivakumar, Tomomi Nobashi, and Daniel L Rubin · 2020
Cited alongside, same era.
Ujjwal Baid, Satyam Ghodasara, Suyash Mohan, Michel Bilello, Evan Calabrese, Errol Colak, Keyvan Farahani, Jayashree Kalpathy-Cramer, Felipe C Kitamura, Sarthak Pati, et al · 2021
Cited alongside, same era.
Scaling the u-net: segmentation of biodegradable bone implants in high-resolution synchrotron radiation microtomograms
Ivo M Baltruschat, Hanna Ćwieka, Diana Krüger, Berit Zeller-Plumhoff, Frank Schlünzen, Regine Willumeit-Römer, Julian Moosmann, and Philipp Heuser · 2021
Cited alongside, same era.
A whole-body fdg-pet/ct dataset with manually annotated tumor lesions
Sergios Gatidis, Tobias Hepp, Marcel Früh, Christian La Fougère, Konstantin Nikolaou, Christina Pfannenberg, Bernhard Schölkopf, Thomas Küstner, Clemens Cyran, and Daniel Rubin · 2022
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Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images
Ali Hatamizadeh, Vishwesh Nath, Yucheng Tang, Dong Yang, Holger R Roth, and Daguang Xu · 2022
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Unetr: Transformers for 3d medical image segmentation
Ali Hatamizadeh, Yucheng Tang, Vishwesh Nath, Dong Yang, Andriy Myronenko, Bennett Landman, Holger R Roth, and Daguang Xu · 2022
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Adwu-net: adaptive depth and width u-net for medical image segmentation by differentiable neural architecture search
Ziyan Huang, Zehua Wang, Zhikai Yang, and Lixu Gu · 2022
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Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation
Yuanfeng Ji, Haotian Bai, Jie Yang, Chongjian Ge, Ye Zhu, Ruimao Zhang, Zhen Li, Lingyan Zhang, Wanling Ma, Xiang Wan, et al · 2022
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Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
Cited alongside, same era.
Transunet: Transformers make strong encoders for medical image segmentation
Jieneng Chen, Yongyi Lu, Qihang Yu, Xiangde Luo, Ehsan Adeli, Yan Wang, Le Lu, Alan L Yuille, and Yuyin Zhou · 2021
Cited alongside, same era.
An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
Cited alongside, same era.
Meta grayscale adaptive network for 3d integrated renal structures segmentation
Yuting He, Guanyu Yang, Jian Yang, Rongjun Ge, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Huazhong Shu, Jean-Louis Dillenseger, et al · 2021
Cited alongside, same era.
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
Cited alongside, same era.
A computed tomography vertebral segmentation dataset with anatomical variations and multi-vendor scanner data
Hans Liebl, David Schinz, Anjany Sekuboyina, Luca Malagutti, Maximilian T Löffler, Amirhossein Bayat, Malek El Husseini, Giles Tetteh, Katharina Grau, Eva Niederreiter, et al · 2021
Cited alongside, same era.
Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Cited alongside, same era.
Abdomenct-1k: Is abdominal organ segmentation a solved problem?
Jun Ma, Yao Zhang, Song Gu, Cheng Zhu, Cheng Ge, Yichi Zhang, Xingle An, Congcong Wang, Qiyuan Wang, Xin Liu, et al · 2021
Cited alongside, same era.
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Medical image analysis on left atrial lge mri for atrial fibrillation studies: A review
Lei Li, Veronika A Zimmer, Julia A Schnabel, and Xiahai Zhuang · 2022
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Word: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from ct image
Xiangde Luo, Wenjun Liao, Jianghong Xiao, Jieneng Chen, Tao Song, Xiaofan Zhang, Kang Li, Dimitris N Metaxas, Guotai Wang, and Shaoting Zhang · 2022
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Fast and low-gpu-memory abdomen ct organ segmentation: The flare challenge
Jun Ma, Yao Zhang, Song Gu, Xingle An, Zhihe Wang, Cheng Ge, Congcong Wang, Fan Zhang, Yu Wang, Yinan Xu, Shuiping Gou, Franz Thaler, Christian Payer, Darko Štern, Edward G.A. Henderson, Dónal M. McSweeney, Andrew Green, Price Jackson, Lachlan McIntosh, Quoc-Cuong Nguyen, Abdul Qayyum, Pierre-Henri Conze, Ziyan Huang, Ziqi Zhou, Deng-Ping Fan, Huan Xiong, Guoqiang Dong, Qiongjie Zhu, Jian He, and Xiaoping Yang · 2022
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Integrated treatment planning in percutaneous microwave ablation of lung tumors
Haoyu Wang, Hongrui Yi, Jie Liu, and Lixu Gu · 2022
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Totalsegmentator: robust segmentation of 104 anatomical structures in ct images
Jakob Wasserthal, Manfred Meyer, Hanns-Christian Breit, Joshy Cyriac, Shan Yang, and Martin Segeroth · 2022
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Car-net: A deep learning-based deformation model for 3d/2d coronary artery registration
Wei Wu, Jingyang Zhang, Wenjia Peng, Hongzhi Xie, Shuyang Zhang, and Lixu Gu · 2022
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Exploring vanilla u-net for lesion segmentation from whole-body fdg-pet/ct scans
Jin Ye, Haoyu Wang, Ziyan Huang, Zhongying Deng, Yanzhou Su, Can Tu, Qian Wu, Yuncheng Yang, Meng Wei, Jingqi Niu, et al · 2022
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Scaling vision transformers
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer · 2022
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Scaling vision transformers to 22 billion parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, et al · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
Closest in time.