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The Medical Segmentation Decathlon


Jun 10, 2021
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, AnnetteKopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M. Summers, Bram van Ginneken, Michel Bilello, Patrick Bilic, Patrick F. Christ, Richard K. G. Do, Marc J. Gollub, Stephan H. Heckers, Henkjan Huisman, William R. Jarnagin, Maureen K. McHugo, Sandy Napel, Jennifer S. Goli Pernicka, Kawal Rhode, Catalina Tobon-Gomez, Eugene Vorontsov, Henkjan Huisman, James A. Meakin, Sebastien Ourselin, Manuel Wiesenfarth, Pablo Arbelaez, Byeonguk Bae, Sihong Chen, Laura Daza, Jianjiang Feng, Baochun He, Fabian Isensee, Yuanfeng Ji, Fucang Jia, Namkug Kim, Ildoo Kim, Dorit Merhof, Akshay Pai, Beomhee Park, Mathias Perslev, Ramin Rezaiifar, Oliver Rippel, Ignacio Sarasua, Wei Shen, Jaemin Son, Christian Wachinger, Liansheng Wang, Yan Wang, Yingda Xia, Daguang Xu, Zhanwei Xu, Yefeng Zheng, Amber L. Simpson, Lena Maier-Hein, M. Jorge Cardoso


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Common Limitations of Image Processing Metrics: A Picture Story


Apr 13, 2021
Annika Reinke, Matthias Eisenmann, Minu D. Tizabi, Carole H. Sudre, Tim Rädsch, Michela Antonelli, Tal Arbel, Spyridon Bakas, M. Jorge Cardoso, Veronika Cheplygina, Keyvan Farahani, Ben Glocker, Doreen Heckmann-Nötzel, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Jens Kleesiek, Tahsin Kurc, Michal Kozubek, Bennett A. Landman, Geert Litjens, Klaus Maier-Hein, Bjoern Menze, Henning Müller, Jens Petersen, Mauricio Reyes, Nicola Rieke, Bram Stieltjes, Ronald M. Summers, Sotirios A. Tsaftaris, Bram van Ginneken, Annette Kopp-Schneider, Paul Jäger, Lena Maier-Hein

* This is a dynamic paper on limitations of commonly used metrics. The current version discusses segmentation metrics only, while future versions will also include metrics for classification and detection. For missing use cases, comments or questions, please contact [email protected] or [email protected]. Substantial contributions to this document will be acknowledged with a co-authorship 

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Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images -- the [email protected] Challenge 2019


Aug 21, 2020
Zhang Li, Jiehua Zhang, Tao Tan, Xichao Teng, Xiaoliang Sun, Yang Li, Lihong Liu, Yang Xiao, Byungjae Lee, Yilong Li, Qianni Zhang, Shujiao Sun, Yushan Zheng, Junyu Yan, Ni Li, Yiyu Hong, Junsu Ko, Hyun Jung, Yanling Liu, Yu-cheng Chen, Ching-wei Wang, Vladimir Yurovskiy, Pavel Maevskikh, Vahid Khanagha, Yi Jiang, Xiangjun Feng, Zhihong Liu, Daiqiang Li, Peter J. Schüffler, Qifeng Yu, Hui Chen, Yuling Tang, Geert Litjens


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Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels


Jun 05, 2020
Hans Pinckaers, Wouter Bulten, Jeroen van der Laak, Geert Litjens


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Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists


Feb 11, 2020
Wouter Bulten, Maschenka Balkenhol, Jean-Joël Awoumou Belinga, Américo Brilhante, Aslı Çakır, Xavier Farré, Katerina Geronatsiou, Vincent Molinié, Guilherme Pereira, Paromita Roy, Günter Saile, Paulo Salles, Ewout Schaafsma, Joëlle Tschui, Anne-Marie Vos, Hester van Boven, Robert Vink, Jeroen van der Laak, Christina Hulsbergen-van de Kaa, Geert Litjens

* 21 pages, 5 figures 

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Streaming convolutional neural networks for end-to-end learning with multi-megapixel images


Nov 11, 2019
Hans Pinckaers, Bram van Ginneken, Geert Litjens

* In review 

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Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands


Oct 23, 2019
Hans Pinckaers, Geert Litjens

* Accepted to 'Medical Imaging meets NeurIPS' workshop at NeurIPS 2019. Source code available at: https://github.com/DIAGNijmegen/neural-odes-segmentation 

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Automated Gleason Grading of Prostate Biopsies using Deep Learning


Jul 18, 2019
Wouter Bulten, Hans Pinckaers, Hester van Boven, Robert Vink, Thomas de Bel, Bram van Ginneken, Jeroen van der Laak, Christina Hulsbergen-van de Kaa, Geert Litjens

* 13 pages, 6 figures 

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Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification


May 16, 2019
Koen Dercksen, Wouter Bulten, Geert Litjens

* 4 pages, 3 figures, MIDL 2019 extended abstract 

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A large annotated medical image dataset for the development and evaluation of segmentation algorithms


Feb 25, 2019
Amber L. Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello, Keyvan Farahani, Bram van Ginneken, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M. Summers, Patrick Bilic, Patrick F. Christ, Richard K. G. Do, Marc Gollub, Jennifer Golia-Pernicka, Stephan H. Heckers, William R. Jarnagin, Maureen K. McHugo, Sandy Napel, Eugene Vorontsov, Lena Maier-Hein, M. Jorge Cardoso


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Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology


Feb 18, 2019
David Tellez, Geert Litjens, Peter Bandi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak


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Neural Image Compression for Gigapixel Histopathology Image Analysis


Nov 07, 2018
David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi


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Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks


Aug 17, 2018
David Tellez, Maschenka Balkenhol, Irene Otte-Holler, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi

* Accepted to appear in IEEE Transactions on Medical Imaging 

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Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard


Aug 17, 2018
Wouter Bulten, Péter Bándi, Jeffrey Hoven, Rob van de Loo, Johannes Lotz, Nick Weiss, Jeroen van der Laak, Bram van Ginneken, Christina Hulsbergen-van de Kaa, Geert Litjens


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Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders


Apr 19, 2018
Wouter Bulten, Geert Litjens


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Training convolutional neural networks with megapixel images


Apr 16, 2018
Hans Pinckaers, Geert Litjens

* Submitted to MIDL 2018 

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Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study


Mar 14, 2018
Zhang Li, Zheyu Hu, Jiaolong Xu, Tao Tan, Hui Chen, Zhi Duan, Ping Liu, Jun Tang, Guoping Cai, Quchang Ouyang, Yuling Tang, Geert Litjens, Qiang Li


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A Survey on Deep Learning in Medical Image Analysis


Jun 04, 2017
Geert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Mohsen Ghafoorian, Jeroen A. W. M. van der Laak, Bram van Ginneken, Clara I. Sánchez

* Revised survey includes expanded discussion section and reworked introductory section on common deep architectures. Added missed papers from before Feb 1st 2017 

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The importance of stain normalization in colorectal tissue classification with convolutional networks


May 23, 2017
Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak

* Published in Proceedings of IEEE International Symposium on Biomedical Imaging (ISBI) 2017 

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Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images


May 10, 2017
Babak Ehteshami Bejnordi, Guido Zuidhof, Maschenka Balkenhol, Meyke Hermsen, Peter Bult, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak


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Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images


Apr 03, 2017
Péter Bándi, Rob van de Loo, Milad Intezar, Daan Geijs, Francesco Ciompi, Bram van Ginneken, Jeroen van der Laak, Geert Litjens

* Accepted for poster presentation at the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 

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Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities


Oct 29, 2016
Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Inge van Uden, Clara Sanchez, Geert Litjens, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel

* 13 pages, 8 figures 

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