Hibou: A Family of Foundational Vision Transformers for Pathology

Decoupled weight decay regularization, 2019

Ilya Loshchilov and Frank Hutter · 2019

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Pannuke: An open pan-cancer histology dataset for nuclei instance segmentation and classification

Jevgenij Gamper, Navid Alemi Koohbanani, Ksenija Benet, Ali Khuram, and Nasir Rajpoot · 2019

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A review for cervical histopathology image analysis using machine vision approaches

Chen Li, Hao Chen, Xiaoyan Li, N. Xu, Zhijie Hu, Dan Xue, Shouliang Qi, He Ma, Le Zhang, and Hongzan Sun · 2020

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Pannuke dataset extension, insights and baselines

Original

Jevgenij Gamper, Navid Alemi Koohbanani, Simon Graham, Mostafa Jahanifar, Ksenija Benet, Syed Ali Khurram, Ayesha Azam, Katherine Hewitt, and Nasir Rajpoot · 2020

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Transformers in vision: A survey

Salman Hameed Khan, Muzammal Naseer, Munawar Hayat, Syed Waqas Zamir, F. Khan, and M. Shah · 2021

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A survey on vision transformer

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, and D. Tao · 2022

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ibot: Image bert pre-training with online tokenizer, 2022

Jinghao Zhou, Chen Wei, Huiyu Wang, Wei Shen, Cihang Xie, Alan Yuille, and Tao Kong · 2022

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RandStainNA: Learning Stain-Agnostic Features from Histology Slides by Bridging Stain Augmentation and Normalization , page 212–221

Yiqing Shen, Yulin Luo, Dinggang Shen, and Jing Ke · 2022

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Scaling vision transformers to gigapixel images via hierarchical self-supervised learning

Richard J. Chen, Chengkuan Chen, Yicong Li, Tiffany Y. Chen, Andrew D. Trister, Rahul G. Krishnan, and Faisal Mahmood · 2022

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Dinov2: Learning robust visual features without supervision, 2023

Maxime Oquab, Timothée Darcet, Theo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Russell Howes, Po-Yao Huang, Hu Xu, Vasu Sharma, Shang-Wen Li, Wojciech Galuba, Mike Rabbat, Mido Assran, Nicolas Ballas, Gabriel Synnaeve, Ishan Misra, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023

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Scaling self-supervised learning for histopathology with masked image modeling

Alexandre Filiot, Ridouane Ghermi, Antoine Olivier, Paul Jacob, Lucas Fidon, Alice Mac Kain, Charlie Saillard, and Jean-Baptiste Schiratti · 2023

Cited alongside, same era.

Benchmarking self-supervised learning on diverse pathology datasets

Mingu Kang, Heon Song, Seonwook Park, Donggeun Yoo, and Sérgio Pereira · 2023

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Vision transformers need registers, 2023

Timothée Darcet, Maxime Oquab, Julien Mairal, and Piotr Bojanowski · 2023

Virchow: A million-slide digital pathology foundation model, 2024

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Rudolfv: A foundation model by pathologists for pathologists, 2024

Jonas Dippel, Barbara Feulner, Tobias Winterhoff, Simon Schallenberg, Gabriel Dernbach, Andreas Kunft, Stephan Tietz, Timo Milbich, Simon Heinke, Marie-Lisa Eich, Julika Ribbat-Idel, Rosemarie Krupar, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, and Maximilian Alber · 2024

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Rotation-agnostic image representation learning for digital pathology, 2024

Saghir Alfasly, Abubakr Shafique, Peyman Nejat, Jibran Khan, Areej Alsaafin, Ghazal Alabtah, and H. R. Tizhoosh · 2024

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Towards large-scale training of pathology foundation models, 2024

kaiko. ai, Nanne Aben, Edwin D. de Jong, Ioannis Gatopoulos, Nicolas Känzig, Mikhail Karasikov, Axel Lagré, Roman Moser, Joost van Doorn, and Fei Tang · 2024

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