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Following unprecedented success on the natural language tasks, Transformers have been successfully applied to several computer vision problems, achieving state-of-the-art results and prompting researchers to reconsider the supremacy of convolutional neural networks (CNNs) as {de facto} operators.
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The multimodal brain tumor image segmentation benchmark (brats)
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Hayit Greenspan, Bram Van Ginneken, and Ronald M Summers · 2016
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Deep residual learning for image recognition
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3d u-net: learning dense volumetric segmentation from sparse annotation
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Laplacian pyramid reconstruction and refinement for semantic segmentation
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Semi-supervised classification with graph convolutional networks
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Preparing a collection of radiology examinations for distribution and retrieval
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Deep learning with differential privacy
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A baseline for detecting misclassified and out-of-distribution examples in neural networks
Dan Hendrycks and Kevin Gimpel · 2016
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Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks
Paras Lakhani and Baskaran Sundaram · 2017
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Deep learning for brain mri segmentation: state of the art and future directions
Zeynettin Akkus, Alfiia Galimzianova, Assaf Hoogi, Daniel L Rubin, and Bradley J Erickson · 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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Fundamentals of medical imaging
Paul Suetens · 2017
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A survey on deep learning in medical image analysis
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen Awm Van Der Laak, Bram Van Ginneken, and Clara I Sánchez · 2017
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Deep learning for medical image analysis
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Dinggang Shen, Guorong Wu, and Heung-Il Suk · 2017
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Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
Yading Yuan · 2017
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Pyramid scene parsing network
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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 · 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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Linknet: Exploiting encoder representations for efficient semantic segmentation
Abhishek Chaurasia and Eugenio Culurciello · 2017
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Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Qinghua Huang, Yaozhong Luo, and Qiangzhi Zhang · 2017
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Gland segmentation in colon histology images: The glas challenge contest
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A dataset and a technique for generalized nuclear segmentation for computational pathology
Neeraj Kumar, Ruchika Verma, Sanuj Sharma, Surabhi Bhargava, Abhishek Vahadane, and Amit Sethi · 2017
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Deformable convolutional networks
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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
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A curated mammography data set for use in computer-aided detection and diagnosis research
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Low-dose ct for the detection and classification of metastatic liver lesions: results of the 2016 low dose ct grand challenge
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
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Baoyu Jing, Pengtao Xie, and Eric Xing · 2017
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Guy Katz, Clark Barrett, David L Dill, Kyle Julian, and Mykel J Kochenderfer · 2017
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
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Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
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Niftynet: a deep-learning platform for medical imaging
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Attention u-net: Learning where to look for the pancreas
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nnu-net: Self-adapting framework for u-net-based medical image segmentation
Fabian Isensee, Jens Petersen, Andre Klein, David Zimmerer, Paul F Jaeger, Simon Kohl, Jakob Wasserthal, Gregor Koehler, Tobias Norajitra, Sebastian Wirkert, et al · 2018
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Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: Is the problem solved?
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Mobilenetv2: Inverted residuals and linear bottlenecks
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A radiogenomic dataset of non-small cell lung cancer
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Chang Min Hyun, Hwa Pyung Kim, Sung Min Lee, Sungchul Lee, and Jin Keun Seo · 2018
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Yoseob Han and Jong Chul Ye · 2018
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The developing human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction
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Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 2018
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Mr and ct data with multiobserver delineations of organs in the pelvic area—part of the gold atlas project
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Medical image registration in image guided surgery: Issues, challenges and research opportunities
Fakhre Alam, Sami Ur Rahman, Sehat Ullah, and Kamal Gulati · 2018
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V-net: Fully convolutional neural networks for volumetric medical image segmentation. june 2016, 2018
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Radiology objects in context (roco): a multimodal image dataset
Obioma Pelka, Sven Koitka, Johannes Rückert, Felix Nensa, and Christoph M Friedrich · 2018
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Overview of the imageclef 2018 caption prediction tasks
Alba Garcia Seco De Herrera, Carstern Eickhof, Vincent Andrearczyk, and Henning Müller · 2018
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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
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Identifying medical diagnoses and treatable diseases by image-based deep learning
Daniel S Kermany, Michael Goldbaum, Wenjia Cai, Carolina CS Valentim, Huiying Liang, Sally L Baxter, Alex McKeown, Ge Yang, Xiaokang Wu, Fangbing Yan, et al · 2018
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Toward an understanding of adversarial examples in clinical trials
Konstantinos Papangelou, Konstantinos Sechidis, James Weatherall, and Gavin Brown · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin · 2018
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Overview of deep learning in gastrointestinal endoscopy
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Deep learning in medical ultrasound analysis: a review
Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei, Li Liu, Shawn Xiang Li, Dong Ni, and Tianfu Wang · 2019
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An overview of deep learning in medical imaging focusing on mri
Alexander Selvikvåg Lundervold and Arvid Lundervold · 2019
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Stand-alone self-attention in vision models
Prajit Ramachandran, Niki Parmar, Ashish Vaswani, Irwan Bello, Anselm Levskaya, and Jonathon Shlens · 2019
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Attention augmented convolutional networks
Irwan Bello, Barret Zoph, Ashish Vaswani, Jonathon Shlens, and Quoc V Le · 2019
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Saiprasad Ravishankar, Jong Chul Ye, and Jeffrey A Fessler · 2019
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Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
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Deep learning techniques for medical image segmentation: achievements and challenges
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Biomedical imaging and analysis in the age of big data and deep learning [scanning the issue]
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Attention gated networks: Learning to leverage salient regions in medical images
Jo Schlemper, Ozan Oktay, Michiel Schaap, Mattias Heinrich, Bernhard Kainz, Ben Glocker, and Daniel Rueckert · 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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Noel Codella, Veronica Rotemberg, Philipp Tschandl, M Emre Celebi, Stephen Dusza, David Gutman, Brian Helba, Aadi Kalloo, Konstantinos Liopyris, Michael Marchetti, et al · 2019
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Corneal endothelial cells over the past decade: are we missing the mark (er)?
Bert Van den Bogerd, Nadia Zakaria, Bianca Adam, Steffi Matthyssen, Carina Koppen, and Sorcha Ní Dhubhghaill · 2019
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Adaptively sparse transformers
Gonçalo M Correia, Vlad Niculae, and André FT Martins · 2019
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A multidimensional choledoch database and benchmarks for cholangiocarcinoma diagnosis
Qing Zhang, Qingli Li, Guanzhen Yu, Li Sun, Mei Zhou, and Junhao Chu · 2019
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A multi-organ nucleus segmentation challenge
Neeraj Kumar, Ruchika Verma, Deepak Anand, Yanning Zhou, Omer Fahri Onder, Efstratios Tsougenis, Hao Chen, Pheng-Ann Heng, Jiahui Li, Zhiqiang Hu, et al · 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, et al · 2019
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Nucleus segmentation across imaging experiments: the 2018 data science bowl
Juan C Caicedo, Allen Goodman, Kyle W Karhohs, Beth A Cimini, Jeanelle Ackerman, Marzieh Haghighi, CherKeng Heng, Tim Becker, Minh Doan, Claire McQuin, et al · 2019
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Xlsor: A robust and accurate lung segmentor on chest x-rays using criss-cross attention and customized radiorealistic abnormalities generation
You-Bao Tang, Yu-Xing Tang, Jing Xiao, and Ronald M Summers · 2019
Cited alongside, same era.
Federated machine learning: Concept and applications
Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong · 2019
Cited alongside, same era.
Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison
Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, et al · 2019
Cited alongside, same era.
Evaluate the malignancy of pulmonary nodules using the 3-d deep leaky noisy-or network
Fangzhou Liao, Ming Liang, Zhe Li, Xiaolin Hu, and Sen Song · 2019
Cited alongside, same era.
Inverse gans for accelerated mri reconstruction
Dominik Narnhofer, Kerstin Hammernik, Florian Knoll, and Thomas Pock · 2019
Cited alongside, same era.
Self-supervised pre-training of swin transformers for 3d medical image analysis
Yucheng Tang, Dong Yang, Wenqi Li, Holger Roth, Bennett Landman, Daguang Xu, Vishwesh Nath, and Ali Hatamizadeh · 2021
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Yao Chang, Hu Menghan, Zhai Guangtao, and Zhang Xiao-Ping · 2021
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Levit: a vision transformer in convnet’s clothing for faster inference
Ben Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, and Matthijs Douze · 2021
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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Mimic-cxr-jpg, a large publicly available database of labeled chest radiographs
Alistair EW Johnson, Tom J Pollard, Nathaniel R Greenbaum, Matthew P Lungren, Chih-ying Deng, Yifan Peng, Zhiyong Lu, Roger G Mark, Seth J Berkowitz, and Steven Horng · 2019
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Knowledge-driven encode, retrieve, paraphrase for medical image report generation
Christy Y Li, Xiaodan Liang, Zhiting Hu, and Eric P Xing · 2019
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Encoder-agnostic adaptation for conditional language generation
Zachary M Ziegler, Luke Melas-Kyriazi, Sebastian Gehrmann, and Alexander M Rush · 2019
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A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy
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Multi-centre, multi-vendor and multi-disease cardiac segmentation: the m&ms challenge
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Ds-transunet: Dual swin transformer u-net for medical image segmentation
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National lung screening trial - the cancer data assess system · 2022
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https://www.kaggle.com/c/diabetic-retinopathy-detection
Diabetic retinopathy challenge · 2022
Closest in time.
https://github.com/OpenMined
To lower the barrier to entry to privacy preserving technology · 2022
Closest in time.