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For medical image segmentation, contrastive learning is the dominant practice to improve the quality of visual representations by contrasting semantically similar and dissimilar pairs of samples.
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U-net: Convolutional networks for biomedical image segmentation
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V-net: Fully convolutional neural networks for volumetric medical image segmentation
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Multi-scale patch and multi-modality atlases for whole heart segmentation of mri
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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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Pyramid scene parsing network
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Antti Tarvainen and Harri Valpola · 2017
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Alex Kendall and Yarin Gal · 2017
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Carl Doersch and Andrew Zisserman · 2017
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Deep adversarial networks for biomedical image segmentation utilizing unannotated images
Yizhe Zhang, Lin Yang, Jianxu Chen, Maridel Fredericksen, David P Hughes, and Danny Z Chen · 2017
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Feature pyramid networks for object detection
Tsung-Yi Lin, Piotr Dollár, Ross Girshick, Kaiming He, Bharath Hariharan, and Serge Belongie · 2017
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Gagandeep Singh, Timon Gehr, Matthew Mirman, Markus Püschel, and Martin Vechev · 2018
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Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Encoder-decoder with atrous separable convolution for semantic image segmentation
Liang-Chieh Chen, Yukun Zhu, George Papandreou, Florian Schroff, and Hartwig Adam · 2018
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Drinet for medical image segmentation
Liang Chen, Paul Bentley, Kensaku Mori, Kazunari Misawa, Michitaka Fujiwara, and Daniel Rueckert · 2018
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Tianyu Hua, Wenxiao Wang, Zihui Xue, Sucheng Ren, Yue Wang, and Hang Zhao · 2021
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Li Jing, Pascal Vincent, Yann LeCun, and Yuandong Tian · 2021
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Improving contrastive learning on imbalanced data via open-world sampling
Ziyu Jiang, Tianlong Chen, Ting Chen, and Zhangyang Wang · 2021
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Isd: Self-supervised learning by iterative similarity distillation
Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai, Paolo Favaro, and Hamed Pirsiavash · 2021
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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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Asdnet: Attention based semi-supervised deep networks for medical image segmentation
Dong Nie, Yaozong Gao, Li Wang, and Dinggang Shen · 2018
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Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved?
Olivier Bernard, Alain Lalande, Clement Zotti, Frederick Cervenansky, Xin Yang, Pheng-Ann Heng, Irem Cetin, Karim Lekadir, Oscar Camara, Miguel Angel Gonzalez Ballester, et al · 2018
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Adrien Bardes, Jean Ponce, and Yann LeCun · 2021
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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
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Unetr: Transformers for 3d medical image segmentation
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Marginal loss and exclusion loss for partially supervised multi-organ segmentation
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A semi-supervised learning for segmentation of gigapixel histopathology images from brain tissues
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Joint semi-supervised and active learning for segmentation of gigapixel pathology images with cost-effective labeling
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Efficient semi-supervised gross target volume of nasopharyngeal carcinoma segmentation via uncertainty rectified pyramid consistency
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Every annotation counts: Multi-label deep supervision for medical image segmentation
Simon Reiß, Constantin Seibold, Alexander Freytag, Erik Rodner, and Rainer Stiefelhagen · 2021
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Semi-supervised semantic segmentation with cross pseudo supervision
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Krishna Chaitanya, Ertunc Erdil, Neerav Karani, and Ender Konukoglu · 2021
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Intriguing properties of contrastive losses
Ting Chen, Calvin Luo, and Lala Li · 2021
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A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging
Zhaohan Xiong, Qing Xia, Zhiqiang Hu, Ning Huang, Cheng Bian, Yefeng Zheng, Sulaiman Vesal, Nishant Ravikumar, Andreas Maier, Xin Yang, et al · 2021
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Semi-supervised left atrium segmentation with mutual consistency training
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Bootstrapping semantic segmentation with regional contrast
Shikun Liu, Shuaifeng Zhi, Edward Johns, and Andrew J Davison · 2021
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Class-aware adversarial transformers for medical image segmentation
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Mutual consistency learning for semi-supervised medical image segmentation
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Sam: Self-supervised learning of pixel-wise anatomical embeddings in radiological images
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Momentum contrastive voxel-wise representation learning for semi-supervised volumetric medical image segmentation
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Information-guided pixel augmentation for pixel-wise contrastive learning
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