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We present DiffInfinite, a hierarchical diffusion model that generates arbitrarily large histological images while preserving long-range correlation structural information.
Texture synthesis by non-parametric sampling
Alexei A Efros and Thomas K Leung · 1999
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Fast texture synthesis using tree-structured vector quantization
Li-Yi Wei and Marc Levoy · 2000
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Image inpainting
Marcelo Bertalmio, Guillermo Sapiro, Vincent Caselles, and Coloma Ballester · 2000
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Real-time texture synthesis by patch-based sampling
Lin Liang, Ce Liu, Ying-Qing Xu, Baining Guo, and Heung-Yeung Shum · 2001
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Image inpainting by patch propagation using patch sparsity
Zongben Xu and Jian Sun · 2010
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krahenbuhl, Jeff Donahue, Trevor Darrell, and Alexei A Efros · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen · 2016
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Unsupervised histopathology image synthesis
Le Hou, Ayush Agarwal, Dimitris Samaras, Tahsin M Kurc, Rajarsi R Gupta, and Joel H Saltz · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Deep image prior
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
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Generative image inpainting with contextual attention
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2018
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Painting outside the box: Image outpainting with gans
Mark Sabini and Gili Rusak · 2018
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Shane T. Barratt and Rishi Sharma · 2018
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100,000 histological images of human colorectal cancer and healthy tissue, April 2018
Jakob Nikolas Kather, Niels Halama, and Alexander Marx · 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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Identification of anonymous mri research participants with face-recognition software
Christopher G Schwarz, Walter K Kremers, Terry M Therneau, Richard R Sharp, Jeffrey L Gunter, Prashanthi Vemuri, Arvin Arani, Anthony J Spychalla, Kejal Kantarci, David S Knopman, et al · 2019
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Free-form image inpainting with gated convolution
Jiahui Yu, Zhe Lin, Jimei Yang, Xiaohui Shen, Xin Lu, and Thomas S Huang · 2019
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Image outpainting and harmonization using generative adversarial networks
Basile Van Hoorick · 2019
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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Resolving challenges in deep learning-based analyses of histopathological images using explanation methods
Miriam Hägele, Philipp Seegerer, Sebastian Lapuschkin, Michael Bockmayr, Wojciech Samek, Frederick Klauschen, Klaus-Robert Müller, and Alexander Binder · 2020
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The future of digital health with federated learning
Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletari, Holger R Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N Galtier, Bennett A Landman, Klaus Maier-Hein, et al · 2020
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Ml4h auditing: From paper to practice
Luis Oala, Jana Fehr, Luca Gilli, Pradeep Balachandran, Alixandro Werneck Leite, Saul Calderon-Ramirez, Danny Xie Li, Gabriel Nobis, Erick Alejandro Muñoz Alvarado, Giovanna Jaramillo-Gutierrez, Christian Matek, Arun Shroff, Ferath Kherif, Bruno Sanguinetti, and Thomas Wiegand · 2020
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Red-gan: Attacking class imbalance via conditioned generation. yet another medical imaging perspective
Ahmad B Qasim, Ivan Ezhov, Suprosanna Shit, Oliver Schoppe, Johannes C Paetzold, Anjany Sekuboyina, Florian Kofler, Jana Lipkova, Hongwei Li, and Bjoern Menze · 2020
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Synthesis of diagnostic quality cancer pathology images by generative adversarial networks
Adrian B Levine, Jason Peng, David Farnell, Mitchell Nursey, Yiping Wang, Julia R Naso, Hezhen Ren, Hossein Farahani, Colin Chen, Derek Chiu, Aline Talhouk, Brandon Sheffield, Maziar Riazy, Philip P Ip, Carlos Parra-Herran, Anne Mills, Naveena Singh, Basile Tessier-Cloutier, Taylor Salisbury, Jonathan Lee, Tim Salcudean, Steven JM Jones, David G Huntsman, C Blake Gilks, Stephen Yip, and Ali Bashashati · 2020
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Prior guided gan based semantic inpainting
Avisek Lahiri, Arnav Kumar Jain, Sanskar Agrawal, Pabitra Mitra, and Prabir Kumar Biswas · 2020
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Guidance and evaluation: Semantic-aware image inpainting for mixed scenes
Liang Liao, Jing Xiao, Zheng Wang, Chia-Wen Lin, and Shin’ichi Satoh · 2020
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Vcnet: A robust approach to blind image inpainting
Yi Wang, Ying-Cong Chen, Xin Tao, and Jiaya Jia · 2020
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Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
A non-parametric test to detect data-copying in generative models
Casey Meehan, Kamalika Chaudhuri, and Sanjoy Dasgupta · 2020
Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models
Ahmed Alaa, Boris Van Breugel, Evgeny S Saveliev, and Mihaela van der Schaar · 2022
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Measuring forgetting of memorized training examples
Matthew Jagielski, Om Thakkar, Florian Tramer, Daphne Ippolito, Katherine Lee, Nicholas Carlini, Eric Wallace, Shuang Song, Abhradeep Thakurta, Nicolas Papernot, et al · 2022
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
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Cited alongside, same era.
Introducing hann windows for reducing edge-effects in patch-based image segmentation
Nicolas Pielawski and Carolina Wählby · 2020
Cited alongside, same era.
Diagnostic accuracy of deep learning in medical imaging: a systematic review and meta-analysis
Ravi Aggarwal, Viknesh Sounderajah, Guy Martin, Daniel SW Ting, Alan Karthikesalingam, Dominic King, Hutan Ashrafian, and Ara Darzi · 2021
Cited alongside, same era.
Selective synthetic augmentation with histogan for improved histopathology image classification
Yuan Xue, Jiarong Ye, Qianying Zhou, L Rodney Long, Sameer Antani, Zhiyun Xue, Carl Cornwell, Richard Zaino, Keith C Cheng, and Xiaolei Huang · 2021
Cited alongside, same era.
PathologyGAN: learning deep representations of cancer tissue
Adalberto Claudio Quiros, Roderick Murray-Smith, and Ke Yuan · 2021
Cited alongside, same era.
Synthetic data in machine learning for medicine and healthcare
Richard Chen, Ming Lu, Tiffany Chen, Drew Williamson, and Faisal Mahmood · 2021
Cited alongside, same era.
Large scale image completion via co-modulated generative adversarial networks
Shengyu Zhao, Jonathan Cui, Yilun Sheng, Yue Dong, Xiao Liang, Eric I Chang, and Yan Xu · 2021
Cited alongside, same era.
Jonathan Ho and Tim Salimans · 2022
Later among the works it cites.
A morphology focused diffusion probabilistic model for synthesis of histopathology images
Puria Azadi Moghadam, Sanne Van Dalen, Karina C. Martin, Jochen Lennerz, Stephen Yip, Hossein Farahani, and Ali Bashashati · 2022
Later among the works it cites.
From modern cnns to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology
Maximilian Springenberg, Annika Frommholz, Markus Wenzel, Eva Weicken, Jackie Ma, and Nils Strodthoff · 2023
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Seggpt: Segmenting everything in context
Xinlong Wang, Xiaosong Zhang, Yue Cao, Wen Wang, Chunhua Shen, and Tiejun Huang · 2023
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Segment anything in medical images
Jun Ma and Bo Wang · 2023
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Data models for dataset drift controls in machine learning with optical images
Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis, Yoan Neuenschwander, Michèle Buck, Christian Matek, Jerome Extermann, Enrico Pomarico, Wojciech Samek, Roderick Murray-Smith, Christoph Clausen, and Bruno Sanguinetti · 2023
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Deep learning generates synthetic cancer histology for explainability and education
James M Dolezal, Rachelle Wolk, Hanna M Hieromnimon, Frederick M Howard, Andrew Srisuwananukorn, Dmitry Karpeyev, Siddhi Ramesh, Sara Kochanny, Jung Woo Kwon, Meghana Agni, et al · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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Diffcollage: Parallel generation of large content with diffusion models
Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, and Ming-Yu Liu · 2023
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∞ \infty -diff: Infinite resolution diffusion with subsampled mollified states, 2023
Sam Bond-Taylor and Chris G. Willcocks · 2023
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Diffusion art or digital forgery? investigating data replication in diffusion models
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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Extracting training data from diffusion models
Nicholas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramer, Borja Balle, Daphne Ippolito, and Eric Wallace · 2023
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Provable copyright protection for generative models
Nikhil Vyas, Sham Kakade, and Boaz Barak · 2023
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Metrological machine learning (2ML)
Luis Oala · 2023
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The role of imagenet classes in fréchet inception distance
Tuomas Kynkäänniemi, Tero Karras, Miika Aittala, Timo Aila, and Jaakko Lehtinen · 2023
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Nasdm: Nuclei-aware semantic histopathology image generation using diffusion models
Aman Shrivastava and P Thomas Fletcher · 2023
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Aligning synthetic medical images with clinical knowledge using human feedback
Shenghuan Sun, Gregory M Goldgof, Atul Butte, and Ahmed M Alaa · 2023
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Self-alignment with instruction backtranslation
Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, and Mike Lewis · 2023
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The curse of recursion: Training on generated data makes models forget
Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson · 2023
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Privacy risks of whole-slide image sharing in digital pathology
Petr Holub, Heimo Müller, Tomáš Bíl, Luca Pireddu, Markus Plass, Fabian Prasser, Irene Schlünder, Kurt Zatloukal, Rudolf Nenutil, and Tomáš Brázdil · 2023
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Feature likelihood score: Evaluating generalization of generative models using samples, 2023
Marco Jiralerspong, Avishek Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, and Gauthier Gidel · 2023
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