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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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Deep Clustering Activation Maps for Emphysema Subtyping


Jun 01, 2021
Weiyi Xie, Colin Jacobs, Bram van Ginneken


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Dense Regression Activation Maps For Lesion Segmentation in CT scans of COVID-19 patients


May 25, 2021
Weiyi Xie, Colin Jacobs, Bram van Ginneken


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Automated Estimation of Total Lung Volume using Chest Radiographs and Deep Learning


May 03, 2021
Ecem Sogancioglu, Keelin Murphy, Ernst Th. Scholten, Luuk H. Boulogne, Mathias Prokop, Bram van Ginneken

* Under review 

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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 with robustness to missing data: A novel approach to the detection of COVID-19


Mar 25, 2021
Erdi Çallı, Keelin Murphy, Steef Kurstjens, Tijs Samson, Robert Herpers, Henk Smits, Matthieu Rutten, Bram van Ginneken


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Deep Learning for Chest X-ray Analysis: A Survey


Mar 15, 2021
Ecem Sogancioglu, Erdi Çallı, Bram van Ginneken, Kicky G. van Leeuwen, Keelin Murphy

* Under review in Medical Image Analysis 

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Adversarial cycle-consistent synthesis of cerebral microbleeds for data augmentation


Jan 16, 2021
Khrystyna Faryna, Kevin Koschmieder, Marcella M. Paul, Thomas van den Heuvel, Anke van der Eerden, Rashindra Manniesing, Bram van Ginneken

* Accepted in Medical Imaging meets NIPS Workshop, NIPS 2020 

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Constraining Volume Change in Learned Image Registration for Lung CTs


Nov 29, 2020
Alessa Hering, Stephanie Häger, Jan Moltz, Nikolas Lessmann, Stefan Heldmann, Bram van Ginneken


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Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI


Sep 23, 2020
Anneke Meyer, Grzegorz Chlebus, Marko Rak, Daniel Schindele, Martin Schostak, Bram van Ginneken, Andrea Schenk, Hans Meine, Horst K. Hahn, Andreas Schreiber, Christian Hansen

* Submitted to Elsevier Computer Methods and Programs in Biomedicine. Anneke Meyer and Grzegorz Chlebus contributed equally to this work. Sourcecode and data available at https://github.com/AnnekeMeyer/AnisotropicMultiStreamCNN 

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Improving Automated COVID-19 Grading with Convolutional Neural Networks in Computed Tomography Scans: An Ablation Study


Sep 21, 2020
Coen de Vente, Luuk H. Boulogne, Kiran Vaidhya Venkadesh, Cheryl Sital, Nikolas Lessmann, Colin Jacobs, Clara I. Sánchez, Bram van Ginneken

* 9 pages, 6 figures 

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A review of deep learning in medical imaging: Image traits, technology trends, case studies with progress highlights, and future promises


Aug 02, 2020
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos, James S. Duncan, Bram van Ginneken, Anant Madabhushi, Jerry L. Prince, Daniel Rueckert, Ronald M. Summers

* 19 pages, 7 figures 

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Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors


Jun 12, 2020
Suzanne C. Wetstein, Cristina González-Gonzalo, Gerda Bortsova, Bart Liefers, Florian Dubost, Ioannis Katramados, Laurens Hogeweg, Bram van Ginneken, Josien P. W. Pluim, Marleen de Bruijne, Clara I. Sánchez, Mitko Veta

* First three authors contributed equally 

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Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans


May 12, 2020
Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier, Bram van Ginneken


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Contextual Two-Stage U-Nets for Robust Pulmonary Lobe Segmentation in CT Scans of COVID-19 and COPD Patients


Apr 19, 2020
Weiyi Xie, Colin Jacobs, Jean-Paul Charbonnier, Bram van Ginneken


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Random smooth gray value transformations for cross modality learning with gray value invariant networks


Mar 13, 2020
Nikolas Lessmann, Bram van Ginneken


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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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BIAS: Transparent reporting of biomedical image analysis challenges


Oct 23, 2019
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning MĂĽller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider, Bennett Landman

* 4 Supplements: Suppl 1: Reviewer checklist Suppl 2: Gloassary Suppl 3: Form for summarizing information on challenge organization Suppl 4: Structured description of a challenge design 

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Iterative augmentation of visual evidence for weakly-supervised lesion localization in deep interpretability frameworks


Oct 16, 2019
Cristina González-Gonzalo, Bart Liefers, Bram van Ginneken, Clara I. Sánchez


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Function Follows Form: Regression from Complete Thoracic Computed Tomography Scans


Sep 27, 2019
Max Argus, Cornelia Schaefer-Prokop, David A. Lynch, Bram van Ginneken


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mlVIRNET: Multilevel Variational Image Registration Network


Sep 22, 2019
Alessa Hering, Bram van Ginneken, Stefan Heldmann

* accepted for publication at MICCAI 2019 

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A deep learning model for segmentation of geographic atrophy to study its long-term natural history


Aug 15, 2019
Bart Liefers, Johanna M. Colijn, Cristina González-Gonzalo, Timo Verzijden, Paul Mitchell, Carel B. Hoyng, Bram van Ginneken, Caroline C. W. Klaver, Clara I. Sánchez

* 22 pages, 3 tables, 4 figures, 1 supplemental figure 

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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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FRODO: Free rejection of out-of-distribution samples: application to chest x-ray analysis


Jul 02, 2019
Erdi Çallı, Keelin Murphy, Ecem Sogancioglu, Bram van Ginneken


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Evaluation of a deep learning system for the joint automated detection of diabetic retinopathy and age-related macular degeneration


Mar 22, 2019
Cristina González-Gonzalo, Verónica Sánchez-Gutiérrez, Paula Hernández-Martínez, Inés Contreras, Yara T. Lechanteur, Artin Domanian, Bram van Ginneken, Clara I. Sánchez


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Computer aided detection of tuberculosis on chest radiographs: An evaluation of the CAD4TB v6 system


Mar 08, 2019
Keelin Murphy, Shifa Salman Habib, Syed Mohammad Asad Zaidi, Saira Khowaja, Aamir Khan, Jaime Melendez, Ernst T. Scholten, Farhan Amad, Steven Schalekamp, Maurits Verhagen, Rick H. H. M. Philipsen, Annet Meijers, Bram van Ginneken


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