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ORCIDGeert Litjens 0001
Geert J. S. Litjens
Person information
- affiliation: Radboud University Medical Center, Diagnostic Image Analysis Group and the Department of Pathology, Nijmegen, The Netherlands
Other persons with the same name
- Geert Litjens 0002 — Utrecht University, Copernicus Institute for Sustainable Development, Utrecht, The Netherlands
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2020 – today
- 2024
[j25]Khrystyna Faryna, Jeroen van der Laak
, Geert Litjens:
Automatic data augmentation to improve generalization of deep learning in H&E stained histopathology. Comput. Biol. Medicine 170: 108018 (2024)- [j24]Daan J. Geijs, Stephan Dooper, Witali Aswolinskiy, Lisa M. Hillen, Avital L. Amir, Geert Litjens:
Detection and subtyping of basal cell carcinoma in whole-slide histopathology using weakly-supervised learning. Medical Image Anal. 93: 103063 (2024) - [j23]Jasper Linmans, Gabriel Raya, Jeroen van der Laak, Geert Litjens:
Diffusion models for out-of-distribution detection in digital pathology. Medical Image Anal. 93: 103088 (2024) - [j22]Jasper Linmans, Emiel Hoogeboom, Jeroen van der Laak, Geert Litjens:
The Latent Doctor Model for Modeling Inter-Observer Variability. IEEE J. Biomed. Health Informatics 28(1): 343-354 (2024) - [i29]Nadieh Khalili, Joey Spronck, Francesco Ciompi, Jeroen van der Laak, Geert Litjens:
Uncertainty-guided annotation enhances segmentation with the human-in-the-loop. CoRR abs/2404.07208 (2024) - [i28]Clément Grisi, Geert Litjens, Jeroen van der Laak:
Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers. CoRR abs/2404.18152 (2024) - 2023
- [j21]Jasper Linmans, Stefan Elfwing, Jeroen van der Laak, Geert Litjens:
Predictive uncertainty estimation for out-of-distribution detection in digital pathology. Medical Image Anal. 83: 102655 (2023) - [j20]Péter Bándi, Maschenka Balkenhol, Marcory Van Dijk, Michel Kok, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
Continual learning strategies for cancer-independent detection of lymph node metastases. Medical Image Anal. 85: 102755 (2023) - [j19]Stephan Dooper, Hans Pinckaers, Witali Aswolinskiy, Konnie M. Hebeda, Sofia Jarkman, Jeroen van der Laak, Geert Litjens:
Gigapixel end-to-end training using streaming and attention. Medical Image Anal. 88: 102881 (2023) - [c28]Daan N. Schouten, Geert J. S. Litjens:
PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions. Digital and Computational Pathology 2023 - [i27]Annika Reinke, Minu Tizabi, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Carole H. Sudre, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Arriel Benis, Matthew B. Blaschko, Florian Büttner, M. Jorge Cardoso, Veronika Cheplygina, Jianxu Chen, Evangelia Christodoulou, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Luciana Ferrer, Adrian Galdran, Bram van Ginneken, Ben Glocker, Patrick Godau, Robert Haase, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Fabian Isensee, Pierre Jannin, Charles E. Kahn, Dagmar Kainmueller, Bernhard Kainz, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Jens Kleesiek, Florian Kofler, Thijs Kooi, Annette Kopp-Schneider, Michal Kozubek, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, Karel G. M. Moons, Henning Müller, Brennan Nichyporuk, Felix Nickel, Jens Petersen, Susanne M. Rafelski, Nasir M. Rajpoot, Mauricio Reyes, Michael A. Riegler, Nicola Rieke, Julio Saez-Rodriguez, Clara I. Sánchez, Shravya Shetty, Maarten van Smeden, Ronald M. Summers, Abdel A. Taha, Aleksei Tiulpin, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Manuel Wiesenfarth, Ziv R. Yaniv, Paul F. Jäger, Lena Maier-Hein:
Understanding metric-related pitfalls in image analysis validation. CoRR abs/2302.01790 (2023) - [i26]Clément Grisi, Geert Litjens, Jeroen van der Laak:
Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images. CoRR abs/2312.12619 (2023) - 2022
- [j18]Lisa C. Adams, Marcus R. Makowski, Günther Engel, Maximilian Rattunde, Felix Busch, Patrick Asbach, Stefan Markus Niehues, Shankeeth Vinayahalingam, Bram van Ginneken, Geert Litjens, Keno K. Bressem:
Prostate158 - An expert-annotated 3T MRI dataset and algorithm for prostate cancer detection. Comput. Biol. Medicine 148: 105817 (2022) - [j17]Hans Pinckaers, Bram van Ginneken, Geert Litjens:
Streaming Convolutional Neural Networks for End-to-End Learning With Multi-Megapixel Images. IEEE Trans. Pattern Anal. Mach. Intell. 44(3): 1581-1590 (2022) - [c27]Pierpaolo Vendittelli, Esther M. M. Smeets, Geert J. S. Litjens:
Automatic tumour segmentation in H&E-stained whole-slide images of the pancreas. Digital and Computational Pathology 2022 - [i25]Lena Maier-Hein, Annika Reinke, Evangelia Christodoulou, Ben Glocker, Patrick Godau, Fabian Isensee, Jens Kleesiek, Michal Kozubek, Mauricio Reyes, Michael A. Riegler, Manuel Wiesenfarth, Michael Baumgartner, Matthias Eisenmann, Doreen Heckmann-Nötzel, A. Emre Kavur, Tim Rädsch, Minu Dietlinde Tizabi, Laura Ación, Michela Antonelli, Tal Arbel, Spyridon Bakas, Peter Bankhead, Arriel Benis, M. Jorge Cardoso, Veronika Cheplygina, Beth A. Cimini, Gary S. Collins, Keyvan Farahani, Bram van Ginneken, Daniel A. Hashimoto, Michael M. Hoffman, Merel Huisman, Pierre Jannin, Charles E. Kahn, Alexandros Karargyris, Alan Karthikesalingam, Hannes Kenngott, Annette Kopp-Schneider, Anna Kreshuk, Tahsin M. Kurç, Bennett A. Landman, Geert Litjens, Amin Madani, Klaus H. Maier-Hein, Anne L. Martel, Peter Mattson, Erik Meijering, Bjoern H. Menze, David Moher, Karel G. M. Moons, Henning Müller, Felix Nickel, Brennan Nichyporuk, Jens Petersen, Nasir M. Rajpoot, Nicola Rieke, Julio Saez-Rodriguez, Clarisa Sánchez Gutiérrez, Shravya Shetty, Maarten van Smeden, Carole H. Sudre, Ronald M. Summers, Abdel A. Taha, Sotirios A. Tsaftaris, Ben Van Calster, Gaël Varoquaux, Paul F. Jäger:
Metrics reloaded: Pitfalls and recommendations for image analysis validation. CoRR abs/2206.01653 (2022) - [i24]Péter Bándi, Maschenka Balkenhol, Marcory Van Dijk, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
Domain adaptation strategies for cancer-independent detection of lymph node metastases. CoRR abs/2207.06193 (2022) - 2021
- [j16]Thomas de Bel, John-Melle Bokhorst, Jeroen van der Laak, Geert Litjens:
Residual cyclegan for robust domain transformation of histopathological tissue slides. Medical Image Anal. 70: 102004 (2021) - [j15]David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Neural Image Compression for Gigapixel Histopathology Image Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 43(2): 567-578 (2021) - [j14]Zhang Li, Jiehua Zhang, Tao Tan, Xichao Teng, Xiaoliang Sun, Hong Zhao, 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, Li Yu, Zhihong Liu, Daiqiang Li, Peter J. Schüffler, Qifeng Yu, Hui Chen, Yuling Tang, Geert Litjens:
Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images - The ACDC@LungHP Challenge 2019. IEEE J. Biomed. Health Informatics 25(2): 429-440 (2021) - [j13]Hans Pinckaers, Wouter Bulten, Jeroen van der Laak, Geert Litjens:
Detection of Prostate Cancer in Whole-Slide Images Through End-to-End Training With Image-Level Labels. IEEE Trans. Medical Imaging 40(7): 1817-1826 (2021) - [c26]Khrystyna Faryna, Jeroen van der Laak, Geert Litjens:
Tailoring automated data augmentation to H&E-stained histopathology. MIDL 2021: 168-178 - [c25]Daan J. Geijs, Hans Pinckaers, Avital L. Amir, Geert J. S. Litjens:
End-to-end classification on basal-cell carcinoma histopathology whole-slides images. Digital Pathology 2021 - [i23]Annika Reinke, Matthias Eisenmann, Minu Dietlinde 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 M. Kurç, Michal Kozubek, Bennett A. Landman, Geert Litjens, Klaus H. Maier-Hein, Bjoern H. 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:
Common Limitations of Image Processing Metrics: A Picture Story. CoRR abs/2104.05642 (2021) - [i22]Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern H. Menze, Olaf Ronneberger, Ronald M. Summers, Bram van Ginneken, Michel Bilello, Patrick Bilic, Patrick Ferdinand Christ, Richard K. G. Do, Marc Gollub, Stephan Heckers, Henkjan J. Huisman, William R. Jarnagin, Maureen McHugo, Sandy Napel, Jennifer Goli-Pernicka, Kawal S. Rhode, Catalina Tobon-Gomez, Eugene Vorontsov, James A. Meakin, Sébastien Ourselin, Manuel Wiesenfarth, Pablo Arbeláez, Byeonguk Bae, Sihong Chen, Laura Alexandra 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:
The Medical Segmentation Decathlon. CoRR abs/2106.05735 (2021) - [i21]Pierpaolo Vendittelli, Esther M. M. Smeets, Geert Litjens:
Automatic tumour segmentation in H&E-stained whole-slide images of the pancreas. CoRR abs/2112.01533 (2021) - 2020
- [c24]Jasper Linmans, Jeroen van der Laak, Geert Litjens:
Efficient Out-of-Distribution Detection in Digital Pathology Using Multi-Head Convolutional Neural Networks. MIDL 2020: 465-478 - [c23]Leander van Eekelen, Hans Pinckaers, Konnie M. Hebeda, Geert Litjens:
Multi-class semantic cell segmentation and classification of aplasia in bone marrow histology images. Digital Pathology 2020: 113200B - [c22]Zaneta Swiderska-Chadaj, Konnie M. Hebeda, Michiel van den Brand, Geert Litjens:
Predicting MYC translocation in HE specimens of diffuse large B-cell lymphoma through deep learning. Digital Pathology 2020: 1132010 - [i20]Wouter Bulten, Maschenka Balkenhol, Jean-Joël Awoumou Belinga, Américo Brilhante, Asli Çakir, 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 A. Hulsbergen van de Kaa, Geert Litjens:
Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists. CoRR abs/2002.04500 (2020) - [i19]Hans Pinckaers, Wouter Bulten, Jeroen van der Laak, Geert Litjens:
Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels. CoRR abs/2006.03394 (2020) - [i18]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:
Deep Learning Methods for Lung Cancer Segmentation in Whole-slide Histopathology Images - the ACDC@LungHP Challenge 2019. CoRR abs/2008.09352 (2020)
2010 – 2019
- 2019
- [j12]Zaneta Swiderska-Chadaj, Hans Pinckaers, Mart van Rijthoven, Maschenka Balkenhol, Margarita Melnikova, Oscar Geessink, Quirine Manson, Mark Sherman, António Polónia, Jeremy Parry, Mustapha Abubakar, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Learning to detect lymphocytes in immunohistochemistry with deep learning. Medical Image Anal. 58 (2019) - [j11]David Tellez, Geert Litjens, Péter Bándi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak:
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. Medical Image Anal. 58 (2019) - [j10]Péter Bándi, Oscar Geessink, Quirine Manson, Marcory Van Dijk, Maschenka Balkenhol, Meyke Hermsen, Babak Ehteshami Bejnordi, Byungjae Lee, Kyunghyun Paeng, Aoxiao Zhong, Quanzheng Li, Farhad Ghazvinian Zanjani, Svitlana Zinger, Keisuke Fukuta, Daisuke Komura, Vlado Ovtcharov, Shenghua Cheng, Shaoqun Zeng, Jeppe Thagaard, Anders B. Dahl, Huangjing Lin, Hao Chen, Ludwig Jacobsson, Martin Hedlund, Melih Çetin, Eren Halici, Hunter Jackson, Richard Chen, Fabian Both, Jörg Franke, Heidi Küsters-Vandevelde, Willem Vreuls, Peter Bult, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge. IEEE Trans. Medical Imaging 38(2): 550-560 (2019) - [c21]Thomas de Bel, Meyke Hermsen, Jesper Kers, Jeroen van der Laak, Geert Litjens:
Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology. MIDL 2019: 151-163 - [c20]Hans Pinckaers, Wouter Bulten, Geert Litjens:
High resolution whole prostate biopsy classification using streaming stochastic gradient descent. Digital Pathology 2019: 109560A - [i17]David Tellez, Geert Litjens, Péter Bándi, Wouter Bulten, John-Melle Bokhorst, Francesco Ciompi, Jeroen van der Laak:
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology. CoRR abs/1902.06543 (2019) - [i16]Amber L. Simpson, Michela Antonelli, Spyridon Bakas, Michel Bilello, Keyvan Farahani, Bram van Ginneken, Annette Kopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern H. Menze, Olaf Ronneberger, Ronald M. Summers, Patrick Bilic, Patrick Ferdinand Christ, Richard K. G. Do, Marc Gollub, Jennifer Golia-Pernicka, Stephan Heckers, William R. Jarnagin, Maureen McHugo, Sandy Napel, Eugene Vorontsov, Lena Maier-Hein, M. Jorge Cardoso:
A large annotated medical image dataset for the development and evaluation of segmentation algorithms. CoRR abs/1902.09063 (2019) - [i15]Koen Dercksen, Wouter Bulten, Geert Litjens:
Dealing with Label Scarcity in Computational Pathology: A Use Case in Prostate Cancer Classification. CoRR abs/1905.06820 (2019) - [i14]Wouter Bulten, Hans Pinckaers, Hester van Boven, Robert Vink, Thomas de Bel, Bram van Ginneken, Jeroen van der Laak, Christina A. Hulsbergen van de Kaa, Geert Litjens:
Automated Gleason Grading of Prostate Biopsies using Deep Learning. CoRR abs/1907.07980 (2019) - [i13]Hans Pinckaers, Geert Litjens:
Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands. CoRR abs/1910.10470 (2019) - [i12]Hans Pinckaers, Bram van Ginneken, Geert Litjens:
Streaming convolutional neural networks for end-to-end learning with multi-megapixel images. CoRR abs/1911.04432 (2019) - 2018
- [j9]David Tellez, Maschenka Balkenhol, Irene Otte-Höller, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. IEEE Trans. Medical Imaging 37(9): 2126-2136 (2018) - [c19]Thomas de Bel, Meyke Hermsen, Geert Litjens, Jeroen van der Laak:
Structure Instance Segmentation in Renal Tissue: A Case Study on Tubular Immune Cell Detection. COMPAY/OMIA@MICCAI 2018: 112-119 - [c18]Wouter Bulten, Christina A. Hulsbergen van de Kaa, Jeroen van der Laak, Geert J. S. Litjens:
Automated segmentation of epithelial tissue in prostatectomy slides using deep learning. Digital Pathology 2018: 105810S - [c17]Daan J. Geijs, Milad Intezar, Jeroen A. W. M. van der Laak, Geert J. S. Litjens:
Automatic color unmixing of IHC stained whole slide images. Digital Pathology 2018: 105810L - [c16]David Tellez, Maschenka Balkenhol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection. Digital Pathology 2018: 105810Z - [c15]Thomas de Bel, Meyke Hermsen, Bart Smeets, Luuk Hilbrands, Jeroen van der Laak, Geert Litjens:
Automatic segmentation of histopathological slides of renal tissue using deep learning. Digital Pathology 2018: 1058112 - [i11]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:
Computer-aided diagnosis of lung carcinoma using deep learning - a pilot study. CoRR abs/1803.05471 (2018) - [i10]Hans Pinckaers, Geert J. S. Litjens:
Training convolutional neural networks with megapixel images. CoRR abs/1804.05712 (2018) - [i9]Wouter Bulten, Geert Litjens:
Unsupervised Prostate Cancer Detection on H&E using Convolutional Adversarial Autoencoders. CoRR abs/1804.07098 (2018) - [i8]Wouter Bulten, Péter Bándi, Jeffrey Hoven, Rob van de Loo, Johannes Lotz, Nick Weiss, Jeroen van der Laak, Bram van Ginneken, Christina A. Hulsbergen van de Kaa, Geert Litjens:
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard. CoRR abs/1808.05883 (2018) - [i7]David Tellez, Maschenka Balkenhol, Irene Otte-Höller, Rob van de Loo, Rob Vogels, Peter Bult, Carla Wauters, Willem Vreuls, Suzanne Mol, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks. CoRR abs/1808.05896 (2018) - [i6]David Tellez, Geert Litjens, Jeroen van der Laak, Francesco Ciompi:
Neural Image Compression for Gigapixel Histopathology Image Analysis. CoRR abs/1811.02840 (2018) - 2017
- [j8]Stefan C. A. Steens, Elise M. Bekers, Willem L. J. Weijs, Geert J. S. Litjens, Andor Veltien, Arie Maat, Guido B. van den Broek, Jeroen A. W. M. van der Laak, Jurgen J. Fütterer, Christina A. Hulsbergen van de Kaa, Matthias A. W. Merkx, Robert P. Takes:
Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR. Int. J. Comput. Assist. Radiol. Surg. 12(5): 821-828 (2017) - [j7]Thijs Kooi, Geert Litjens, Bram van Ginneken, Albert Gubern-Mérida, Clara I. Sánchez, Ritse Mann, Ard den Heeten, Nico Karssemeijer:
Large scale deep learning for computer aided detection of mammographic lesions. Medical Image Anal. 35: 303-312 (2017) - [j6]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:
A survey on deep learning in medical image analysis. Medical Image Anal. 42: 60-88 (2017) - [c14]Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak:
The importance of stain normalization in colorectal tissue classification with convolutional networks. ISBI 2017: 160-163 - [c13]Péter Bándi, Rob van de Loo, Milad Intezar, Daan Geijs, Francesco Ciompi, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
Comparison of different methods for tissue segmentation in histopathological whole-slide images. ISBI 2017: 591-595 - [i5]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:
A Survey on Deep Learning in Medical Image Analysis. CoRR abs/1702.05747 (2017) - [i4]Francesco Ciompi, Oscar Geessink, Babak Ehteshami Bejnordi, Gabriel Silva de Souza, Alexi Baidoshvili, Geert Litjens, Bram van Ginneken, Iris Nagtegaal, Jeroen van der Laak:
The importance of stain normalization in colorectal tissue classification with convolutional networks. CoRR abs/1702.05931 (2017) - [i3]Péter Bándi, Rob van de Loo, Milad Intezar, Daan Geijs, Francesco Ciompi, Bram van Ginneken, Jeroen van der Laak, Geert Litjens:
Comparison of Different Methods for Tissue Segmentation in Histopathological Whole-Slide Images. CoRR abs/1703.05990 (2017) - [i2]Babak Ehteshami Bejnordi, Guido C. A. Zuidhof, Maschenka Balkenhol, Meyke Hermsen, Peter Bult, Bram van Ginneken, Nico Karssemeijer, Geert Litjens, Jeroen van der Laak:
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images. CoRR abs/1705.03678 (2017) - 2016
- [j5]Babak Ehteshami Bejnordi, Geert Litjens, Nadya Timofeeva, Irene Otte-Höller, André Homeyer, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Stain Specific Standardization of Whole-Slide Histopathological Images. IEEE Trans. Medical Imaging 35(2): 404-415 (2016) - [j4]Arnaud Arindra Adiyoso Setio, Francesco Ciompi, Geert Litjens, Paul K. Gerke, Colin Jacobs, Sarah J. van Riel, Mathilde Marie Winkler Wille, Matiullah Naqibullah, Clara I. Sánchez, Bram van Ginneken:
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks. IEEE Trans. Medical Imaging 35(5): 1160-1169 (2016) - [j3]Babak Ehteshami Bejnordi, Maschenka Balkenhol, Geert Litjens, Roland Holland, Peter Bult, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images. IEEE Trans. Medical Imaging 35(9): 2141-2150 (2016) - [c12]Geert Litjens, Kai Safferling, Niels Grabe:
Automated robust registration of grossly misregistered whole-slide images with varying stains. Digital Pathology 2016: 979103 - [i1]Mohsen Ghafoorian, Nico Karssemeijer, Tom Heskes, Inge van Uden, Clara I. Sánchez, Geert Litjens, Frank-Erik de Leeuw, Bram van Ginneken, Elena Marchiori, Bram Platel:
Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities. CoRR abs/1610.04834 (2016) - 2015
- [c11]Babak Ehteshami Bejnordi, Geert Litjens, Meyke Hermsen, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images. Digital Pathology 2015: 94200H - [c10]Geert Litjens, Babak Ehteshami Bejnordi, Nadya Timofeeva, G. Swadi, Iringo Kovacs, Christina A. Hulsbergen van de Kaa, Jeroen van der Laak:
Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens. Digital Pathology 2015: 94200B - 2014
- [j2]Geert Litjens, Robert Toth, Wendy J. M. van de Ven, Caroline Hoeks, Sjoerd Kerkstra, Bram van Ginneken, Graham Vincent, Gwenaël Guillard, Neil Birbeck, Jindang Zhang, Robin Strand, Filip Malmberg, Yangming Ou, Christos Davatzikos, Matthias Kirschner, Florian Jung, Jing Yuan, Wu Qiu, Qinquan Gao, Philip J. Edwards, Bianca Maan, Ferdinand van der Heijden, Soumya Ghose, Jhimli Mitra, Jason Dowling, Dean C. Barratt, Henkjan J. Huisman, Anant Madabhushi:
Evaluation of prostate segmentation algorithms for MRI: The PROMISE12 challenge. Medical Image Anal. 18(2): 359-373 (2014) - [j1]Geert Litjens, Oscar Debats, Jelle O. Barentsz, Nico Karssemeijer, Henkjan J. Huisman:
Computer-Aided Detection of Prostate Cancer in MRI. IEEE Trans. Medical Imaging 33(5): 1083-1092 (2014) - [c9]Geert J. S. Litjens, R. Elliott, Natalie Shih, Michael D. Feldman, Jelle O. Barentsz, Christina A. Hulsbergen van de Kaa, Iringo Kovacs, Henkjan J. Huisman, Anant Madabhushi:
Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI. Computer-Aided Diagnosis 2014: 903512 - [c8]Geert Litjens, Henkjan J. Huisman, R. Elliott, Natalie Shih, Michael D. Feldman, Satish Viswanath, Jurgen J. Fütterer, J. Bomers, Anant Madabhushi:
Distinguishing benign confounding treatment changes from residual prostate cancer on MRI following laser ablation. Image-Guided Procedures 2014: 90361D - 2012
- [c7]Geert J. S. Litjens, Jelle O. Barentsz, Nico Karssemeijer, Henkjan J. Huisman:
Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach. Computer-Aided Diagnosis 2012: 83150G - [c6]Geert Litjens, Oscar Debats, Wendy J. M. van de Ven, Nico Karssemeijer, Henkjan J. Huisman:
A Pattern Recognition Approach to Zonal Segmentation of the Prostate on MRI. MICCAI (2) 2012: 413-420 - 2011
- [c5]Geert J. S. Litjens, Pieter C. Vos, Jelle O. Barentsz, Nico Karssemeijer, Henkjan J. Huisman:
Automatic computer aided detection of abnormalities in multi-parametric prostate MRI. Computer-Aided Diagnosis 2011: 79630T - [c4]Wendy J. M. van de Ven, Geert J. S. Litjens, Jelle O. Barentsz, Thomas Hambrock, Henkjan J. Huisman:
Required Accuracy of MR-US Registration for Prostate Biopsies. Prostate Cancer Imaging 2011: 92-99 - 2010
- [c3]Geert J. S. Litjens, Marieke Heisen, Johannes Buurman, Bart M. ter Haar Romeny:
Pharmacokinetic models in clinical practice: what model to use for DCE-MRI of the breast? ISBI 2010: 185-188 - [c2]Henkjan J. Huisman, Pieter C. Vos, Geert Litjens, Thomas Hambrock, Jelle O. Barentsz:
Computer Aided Detection of Prostate Cancer Using T2, DWI and DCE MRI: Methods and Clinical Applications. Prostate Cancer Imaging 2010: 4-14 - [c1]Geert J. S. Litjens, Laurens Hogeweg, Arnold M. R. Schilham, Pim A. de Jong, Max A. Viergever, Bram van Ginneken:
Simulation of Nodules and Diffuse Infiltrates in Chest Radiographs Using CT Templates. MICCAI (2) 2010: 396-403
Coauthor Index
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