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Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data.
Med3d: Transfer learning for 3d medical image analysis
Sihong Chen, Kai Ma, and Yefeng Zheng · 1904
Earlier work this paper cites.
The quadratic assignment problem
Rainer E Burkard, Eranda Cela, Panos M Pardalos, and Leonidas S Pitsoulis · 1998
Earlier work this paper cites.
Development of a digital image database for chest radiographs with and without a lung nodule: receiver operating characteristic analysis of radiologists’ detection of pulmonary nodules
Junji Shiraishi, Shigehiko Katsuragawa, Junpei Ikezoe, Tsuneo Matsumoto, Takeshi Kobayashi, Ken-ichi Komatsu, Mitate Matsui, Hiroshi Fujita, Yoshie Kodera, and Kunio Doi · 2000
Earlier work this paper cites.
Improved baselines with momentum contrastive learning
Xinlei Chen, Haoqi Fan, Ross Girshick, and Kaiming He · 2003
Earlier work this paper cites.
Ridge-based vessel segmentation in color images of the retina
Joes Staal, Michael D Abràmoff, Meindert Niemeijer, Max A Viergever, and Bram Van Ginneken · 2004
Earlier work this paper cites.
The alzheimer’s disease neuroimaging initiative
Susanne G Mueller, Michael W Weiner, Leon J Thal, Ronald C Petersen, Clifford Jack, William Jagust, John Q Trojanowski, Arthur W Toga, and Laurel Beckett · 2005
Earlier work this paper cites.
Object tracking: A survey
Alper Yilmaz, Omar Javed, and Mubarak Shah · 2006
Earlier work this paper cites.
Probabilistic graph and hypergraph matching
Ron Zass and Amnon Shashua · 2008
Earlier work this paper cites.
Statistical shape models for 3d medical image segmentation: a review
Tobias Heimann and Hans-Peter Meinzer · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Alzheimer’s disease neuroimaging initiative (adni): clinical characterization
Ronald Carl Petersen, Paul S Aisen, Laurel A Beckett, Michael C Donohue, Anthony Collins Gamst, Danielle J Harvey, Clifford R Jack, William J Jagust, Leslie M Shaw, Arthur W Toga, et al · 2010
Earlier work this paper cites.
Perturb-and-map random fields: Using discrete optimization to learn and sample from energy models
George Papandreou and Alan L Yuille · 2011
Earlier work this paper cites.
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
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Earlier work this paper cites.
Computer-aided detection of prostate cancer in mri
Geert Litjens, Oscar Debats, Jelle Barentsz, Nico Karssemeijer, and Henkjan Huisman · 2014
Earlier work this paper cites.
Factorized graph matching
Feng Zhou and Fernando De la Torre · 2015
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Earlier work this paper cites.
Fast r-cnn
Ross Girshick · 2015
Earlier work this paper cites.
Automatic detection of large pulmonary solid nodules in thoracic ct images
Arnaud AA Setio, Colin Jacobs, Jaap Gelderblom, and Bram van Ginneken · 2015
Earlier work this paper cites.
Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation
Holger R Roth, Le Lu, Amal Farag, Hoo-Chang Shin, Jiamin Liu, Evrim B Turkbey, and Ronald M Summers · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Multi-scale patch and multi-modality atlases for whole heart segmentation of mri
Xiahai Zhuang and Juan Shen · 2016
Earlier work this paper cites.
Data from pancreas-ct. the cancer imaging archive
Holger R Roth, Amal Farag, E Turkbey, Le Lu, Jiamin Liu, and Ronald M Summers · 2016
Earlier work this paper cites.
Radiology data from the cancer genome atlas colon adenocarcinoma [tcga-coad] collection
S Kirk, Y Lee, CA Sadow, S Levine, C Roche, E Bonaccio, and J Filiippini · 2016
Earlier work this paper cites.
Radiology data from the cancer genome atlas kidney chromophobe [tcga-kich] collection
MW Linehan, R Gautam, CA Sadow, and S Levine · 2016
Earlier work this paper cites.
Radiology data from the cancer genome atlas kidney renal clear cell carcinoma [tcga-kirc] collection
O Akin, P Elnajjar, M Heller, R Jarosz, B Erickson, S Kirk, and J Filippini · 2016
Earlier work this paper cites.
Radiology data from the cancer genome atlas sarcoma [tcga-sarc] collection
C Roche, E Bonaccio, and J Filippini · 2016
Earlier work this paper cites.
Curated breast imaging subset of ddsm
R Sawyer Lee, F Gimenez, A Hoogi, and D Rubin · 2016
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
Earlier work this paper cites.
A study of lagrangean decompositions and dual ascent solvers for graph matching
Paul Swoboda, Carsten Rother, Hassan Abu Alhaija, Dagmar Kainmuller, and Bogdan Savchynskyy · 2017
Earlier work this paper cites.
Kvasir: A multi-class image dataset for computer aided gastrointestinal disease detection
Konstantin Pogorelov, Kristin Ranheim Randel, Carsten Griwodz, Sigrun Losada Eskeland, Thomas de Lange, Dag Johansen, Concetto Spampinato, Duc-Tien Dang-Nguyen, Mathias Lux, Peter Thelin Schmidt, et al · 2017
Earlier work this paper cites.
Quo vadis, action recognition? a new model and the kinetics dataset
Joao Carreira and Andrew Zisserman · 2017
Earlier work this paper cites.
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer
Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes Van Diest, Bram Van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen AWM Van Der Laak, Meyke Hermsen, Quirine F Manson, Maschenka Balkenhol, et al · 2017
Earlier work this paper cites.
High resolution global gridded data for use in population studies
Christopher T Lloyd, Alessandro Sorichetta, and Andrew J Tatem · 2017
Earlier work this paper cites.
Prostatex challenge data
Geert Litjens, Oscar Debats, Jelle Barentsz, Nico Karssemeijer, and Henkjan Huisman · 2017
Earlier work this paper cites.
Bccd dataset, 2017
Shenggan · 2017
Earlier work this paper cites.
A curated mammography data set for use in computer-aided detection and diagnosis research
Rebecca Sawyer Lee, Francisco Gimenez, Assaf Hoogi, Kanae Kawai Miyake, Mia Gorovoy, and Daniel L Rubin · 2017
Earlier work this paper cites.
Deep clustering for unsupervised learning of visual features
Mathilde Caron, Piotr Bojanowski, Armand Joulin, and Matthijs Douze · 2018
Earlier work this paper cites.
Unsupervised feature learning via non-parametric instance discrimination
Zhirong Wu, Yuanjun Xiong, Stella X Yu, and Dahua Lin · 2018
Earlier work this paper cites.
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
Earlier work this paper cites.
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
Earlier work this paper cites.
A nested u-net architecture for medical image segmentation (2018)
Z Zhou, MMR Siddiquee, N Tajbakhsh, and J UNet+ Liang · 2018
Earlier work this paper cites.
NiftyNet: a deep-learning platform for medical imaging
Eli Gibson, Wenqi Li, Carole Sudre, Lucas Fidon, Dzhoshkun I Shakir, Guotai Wang, Zach Eaton-Rosen, Robert Gray, Tom Doel, Yipeng Hu, et al · 2018
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A framework for identifying diabetic retinopathy based on anti-noise detection and attention-based fusion
Zhiwen Lin, Ruoqian Guo, Yanjie Wang, Bian Wu, Tingting Chen, Wenzhe Wang, Danny Z Chen, and Jian Wu · 2018
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Rotation equivariant CNNs for digital pathology
Bastiaan S Veeling, Jasper Linmans, Jim Winkens, Taco Cohen, and Max Welling · 2018
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Imaging and clinical data archive for head and neck squamous cell carcinoma patients treated with radiotherapy
Aaron J Grossberg, Abdallah SR Mohamed, Hesham Elhalawani, William C Bennett, Kirk E Smith, Tracy S Nolan, Bowman Williams, Sasikarn Chamchod, Jolien Heukelom, Michael E Kantor, et al · 2018
Cited alongside, same era.
Radiomic biomarkers to refine risk models for distant metastasis in hpv-related oropharyngeal carcinoma
Jennifer Yin Yee Kwan, Jie Su, Shao Hui Huang, Laleh S Ghoraie, Wei Xu, Biu Chan, Kenneth W Yip, Meredith Giuliani, Andrew Bayley, John Kim, et al · 2018
Mitoem dataset: Large-scale 3d mitochondria instance segmentation from em images
D. Wei, Z. Lin, D. Barranco, N. Wendt, X. Liu, W. Yin, X. Huang, A. Gupta, W. Jang, X. Wang, I. Arganda-Carreras, J. Lichtman, and H. Pfister · 2020
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Later among the works it cites.
Scaling up visual and vision-language representation learning with noisy text supervision
Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc Le, Yun-Hsuan Sung, Zhen Li, and Tom Duerig · 2021
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Barlow twins: Self-supervised learning via redundancy reduction
Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, and Stéphane Deny · 2021
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Compressive visual representations
Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John Canny, and Ian Fischer · 2021
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Labeled optical coherence tomography (oct) and chest x-ray images for classification
Daniel Kermany, Kang Zhang, Michael Goldbaum, et al · 2018
Cited alongside, same era.
Automated measurement of fetal head circumference using 2d ultrasound images
Thomas LA van den Heuvel, Dagmar de Bruijn, Chris L de Korte, and Bram van Ginneken · 2018
Cited alongside, same era.
Kid-net: convolution networks for kidney vessels segmentation from ct-volumes
Ahmed Taha, Pechin Lo, Junning Li, and Tao Zhao · 2018
Cited alongside, same era.
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Veronika Cheplygina, Marleen de Bruijne, and Josien PW Pluim · 2019
Cited alongside, same era.
Self-supervised feature learning for 3d medical images by playing a rubik’s cube
Xinrui Zhuang, Yuexiang Li, Yifan Hu, Kai Ma, Yujiu Yang, and Yefeng Zheng · 2019
Cited alongside, same era.
Simplifying graph convolutional networks
Felix Wu, Amauri Souza, Tianyi Zhang, Christopher Fifty, Tao Yu, and Kilian Weinberger · 2019
Cited alongside, same era.
Noel Codella, Veronica Rotemberg, Philipp Tschandl, M Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, et al · 2019
Cited alongside, same era.
Region similarity representation learning
Tete Xiao, Colorado J Reed, Xiaolong Wang, Kurt Keutzer, and Trevor Darrell · 2021
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Dense contrastive learning for self-supervised visual pre-training
Xinlong Wang, Rufeng Zhang, Chunhua Shen, Tao Kong, and Lei Li · 2021
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Models genesis
Zongwei Zhou, Vatsal Sodha, Jiaxuan Pang, Michael B Gotway, and Jianming Liang · 2021
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Transferable visual words: Exploiting the semantics of anatomical patterns for self-supervised learning
Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B Gotway, and Jianming Liang · 2021
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On the opportunities and risks of foundation models
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
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Image matching from handcrafted to deep features: A survey
Jiayi Ma, Xingyu Jiang, Aoxiang Fan, Junjun Jiang, and Junchi Yan · 2021
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Implicit MLE: backpropagating through discrete exponential family distributions
Mathias Niepert, Pasquale Minervini, and Luca Franceschi · 2021
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Propagate yourself: Exploring pixel-level consistency for unsupervised visual representation learning
Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, and Han Hu · 2021
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Rv-gan: Segmenting retinal vascular structure in fundus photographs using a novel multi-scale generative adversarial network
Sharif Amit Kamran, Khondker Fariha Hossain, Alireza Tavakkoli, Stewart Lee Zuckerbrod, Kenton M Sanders, and Salah A Baker · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Jcs: An explainable covid-19 diagnosis system by joint classification and segmentation
Yu-Huan Wu, Shang-Hua Gao, Jie Mei, Jun Xu, Deng-Ping Fan, Rong-Guo Zhang, and Ming-Ming Cheng · 2021
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Saras challenge on multi-domain endoscopic surgeon action detection, 2021
Fabio Cuzzolin, Vivek Singh Bawa, Inna Skarga-Bandurova, Mohamed Mohamed, Jackson Ravindran Charles, Elettra Oleari, Alice Leporini, Carmela Landolfo, Armando Stabile, Francesco Setti, et al · 2021
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The saras endoscopic surgeon action detection (esad) dataset: Challenges and methods, 2021
Vivek Singh Bawa, Gurkirt Singh, Francis KapingA, Inna Skarga-Bandurova, Elettra Oleari, Alice Leporini, Carmela Landolfo, Pengfei Zhao, Xi Xiang, Gongning Luo, Kuanquan Wang, Liangzhi Li, Bowen Wang, Shang Zhao, Li Li, Armando Stabile, Francesco Setti, Riccardo Muradore, and Fabio Cuzzolin · 2021
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Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set
Christian Matek, Sebastian Krappe, Christian Münzenmayer, Torsten Haferlach, and Carsten Marr · 2021
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Flava: A foundational language and vision alignment model
Amanpreet Singh, Ronghang Hu, Vedanuj Goswami, Guillaume Couairon, Wojciech Galuba, Marcus Rohrbach, and Douwe Kiela · 2022
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A comparative study of graph matching algorithms in computer vision
Stefan Haller, Lorenz Feineis, Lisa Hutschenreiter, Florian Bernard, Carsten Rother, Dagmar Kainmüller, Paul Swoboda, and Bogdan Savchynskyy · 2022
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Vicregl: Self-supervised learning of local visual features
Adrien Bardes, Jean Ponce, and Yann LeCun · 2022
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Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, and Jovana Mitrovic · 2022
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Unifying visual contrastive learning for object recognition from a graph perspective
Shixiang Tang, Feng Zhu, Lei Bai, Rui Zhao, Chenyu Wang, and Wanli Ouyang · 2022
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On the duality between contrastive and non-contrastive self-supervised learning
Quentin Garrido, Yubei Chen, Adrien Bardes, Laurent Najman, and Yann Lecun · 2022
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Omnivl: One foundation model for image-language and video-language tasks
Junke Wang, Dongdong Chen, Zuxuan Wu, Chong Luo, Luowei Zhou, Yucheng Zhao, Yujia Xie, Ce Liu, Yu-Gang Jiang, and Lu Yuan · 2022
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Unsupervised domain adaptation for point cloud semantic segmentation via graph matching
Yikai Bian, Le Hui, Jianjun Qian, and Jin Xie · 2022
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Gate: graph cca for temporal self-supervised learning for label-efficient fmri analysis
Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, and Xiaoxiao Li · 2022
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Self-supervised learning of visual graph matching
Chang Liu, Shaofeng Zhang, Xiaokang Yang, and Junchi Yan · 2022
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Inscon: instance consistency feature representation via self-supervised learning
Junwei Yang, Ke Zhang, Zhaolin Cui, Jinming Su, Junfeng Luo, and Xiaolin Wei · 2022
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Adaptive perturbation-based gradient estimation for discrete latent variable models
Pasquale Minervini, Luca Franceschi, and Mathias Niepert · 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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Hasan Md Tusfiqur, Duy MH Nguyen, Mai TN Truong, Triet A Nguyen, Binh T Nguyen, Michael Barz, Hans-Juergen Profitlich, Ngoc TT Than, Ngan Le, Pengtao Xie, et al · 2022
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Segment anything model for medical image analysis: an experimental study
Maciej A Mazurowski, Haoyu Dong, Hanxue Gu, Jichen Yang, Nicholas Konz, and Yixin Zhang · 2023
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Accuracy of segment-anything model (sam) in medical image segmentation tasks
Sheng He, Rina Bao, Jingpeng Li, P Ellen Grant, and Yangming Ou · 2023
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Detection recovery in online multi-object tracking with sparse graph tracker
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Conjugate product graphs for globally optimal 2d-3d shape matching
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The liver tumor segmentation benchmark (lits)
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