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2020 – today
- 2024
- [j23]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) - [j22]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) - [j21]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) - [j20]Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Shenghua Cheng, Jiabo Ma, John Pocock, Josien P. W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan-E-Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Xiuli Liu, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi:
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. IEEE J. Biomed. Health Informatics 28(3): 1161-1172 (2024) - [i23]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) - [i22]Clément Grisi, Geert Litjens, Jeroen van der Laak:
Masked Attention as a Mechanism for Improving Interpretability of Vision Transformers. CoRR abs/2404.18152 (2024) - [i21]Artur Jurgas, Marek Wodzinski, Marina D'Amato, Jeroen van der Laak, Manfredo Atzori, Henning Müller:
Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation. CoRR abs/2406.11538 (2024) - 2023
- [j19]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) - [j18]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) - [j17]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) - [c27]Joey Spronck, Thijs Gelton, Leander van Eekelen, Joep Bogaerts, Leslie Tessier, Mart van Rijthoven, Lieke van der Woude, Michel van den Heuvel, Willemijn Theelen, Jeroen van der Laak, Francesco Ciompi:
nnUNet meets pathology: Bridging the gap for application to whole slide images and computational biomarkers. MIDL 2023: 1859-1874 - [i20]Yiping Jiao, Jeroen van der Laak, Shadi Albarqouni, Zhang Li, Tao Tan, Abhir Bhalerao, Jiabo Ma, Jiamei Sun, Johnathon Pocock, Josien P. W. Pluim, Navid Alemi Koohbanani, Raja Muhammad Saad Bashir, Shan E Ahmed Raza, Sibo Liu, Simon Graham, Suzanne C. Wetstein, Syed Ali Khurram, Thomas Watson, Nasir M. Rajpoot, Mitko Veta, Francesco Ciompi:
LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset. CoRR abs/2301.06304 (2023) - [i19]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
- [j16]Niccolò Marini, Stefano Marchesin, Sebastian Otálora, Marek Wodzinski, Alessandro Caputo, Mart van Rijthoven, Witali Aswolinskiy, John-Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Vatrano, Filippo Fraggetta, Jeroen van der Laak, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Müller, Manfredo Atzori:
Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. npj Digit. Medicine 5 (2022) - [i18]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
- [j15]Niccolò Marini, Sebastian Otálora, Damian Podareanu, Mart van Rijthoven, Jeroen van der Laak, Francesco Ciompi, Henning Müller, Manfredo Atzori:
Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images. Frontiers Comput. Sci. 3: 684521 (2021) - [j14]Mart van Rijthoven, Maschenka Balkenhol, Karina Silina, Jeroen van der Laak, Francesco Ciompi:
HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images. Medical Image Anal. 68: 101890 (2021) - [j13]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) - [j12]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) - [j11]Francesco Ciompi, Mitko Veta, Jeroen van der Laak, Nasir M. Rajpoot:
Editorial Computational Pathology. IEEE J. Biomed. Health Informatics 25(2): 303-306 (2021) - [j10]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]Witali Aswolinskiy, David Tellez, Gabriel Raya, Lieke van der Woude, Monika Looijen-Salamon, Jeroen van der Laak, Katrien Grunberg, Francesco Ciompi:
Neural image compression for non-small cell lung cancer subtype classification in H&E stained whole-slide images. Medical Imaging: Digital Pathology 2021 - [c24]Jeroen A. W. M. van der Laak:
Computational Pathology: What is the way forward? Medical Imaging: Digital Pathology 2021 - [c23]Mart van Rijthoven, Maschenka Balkenhol, Manfredo Atzori, Peter Bult, Jeroen van der Laak, Francesco Ciompi:
Few-shot weakly supervised detection and retrieval in histopathology whole-slide images. Medical Imaging: Digital Pathology 2021 - [e2]Manfredo Atzori, Nikolay Burlutskiy, Francesco Ciompi, Zhang Li, Fayyaz A. Minhas, Henning Müller, Tingying Peng, Nasir M. Rajpoot, Ben Torben-Nielsen, Jeroen van der Laak, Mitko Veta, Yinyin Yuan, Inti Zlobec:
MICCAI Workshop on Computational Pathology, COMPAY@MICCAI 2021, 27 September 2021, Virtual Event. Proceedings of Machine Learning Research 156, PMLR 2021 [contents] - [d1]Jeroen van der Laak, Johannes Lotz, Nick Weiss, Stefan Heldmann:
HyReCo - Hybrid re-stained and consecutive histological serial sections. IEEE DataPort, 2021 - [i17]Johannes Lotz, Nick Weiss, Jeroen van der Laak, Stefan Heldmann:
High-resolution Image Registration of Consecutive and Re-stained Sections in Histopathology. CoRR abs/2106.13150 (2021) - [i16]John-Melle Bokhorst, Iris D. Nagtegaal, Filippo Fraggetta, Simona Vatrano, Wilma Mesker, Michael Vieth, Jeroen van der Laak, Francesco Ciompi:
Automated risk classification of colon biopsies based on semantic segmentation of histopathology images. CoRR abs/2109.07892 (2021) - 2020
- [c22]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 - [c21]David Tellez, Diederik Höppener, Cornelis Verhoef, Dirk J. Grünhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi:
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. MIDL 2020: 770-783 - [i15]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) - [i14]David Tellez, Diederik Höppener, Cornelis Verhoef, Dirk J. Grünhagen, Pieter Nierop, Michal Drozdzal, Jeroen van der Laak, Francesco Ciompi:
Extending Unsupervised Neural Image Compression With Supervised Multitask Learning. CoRR abs/2004.07041 (2020) - [i13]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) - [i12]Mart van Rijthoven, Maschenka Balkenhol, Karina Silina, Jeroen van der Laak, Francesco Ciompi:
HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images. CoRR abs/2006.12230 (2020) - [i11]Caner Mercan, Maschenka Balkenhol, Roberto Salgado, Mark Sherman, Philippe Vielh, Willem Vreuls, António Polónia, Hugo M. Horlings, Wilko Weichert, Jodi M. Carter, Peter Bult, Matthias Christgen, Carsten Denkert, Koen van de Vijver, Jeroen van der Laak, Francesco Ciompi:
Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer. CoRR abs/2012.04974 (2020)
2010 – 2019
- 2019
- [j9]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) - [j8]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) - [j7]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) - [c20]John-Melle Bokhorst, Hans Pinckaers, Peter van Zwam, Iris Nagtegaal, Jeroen van der Laak, Francesco Ciompi:
Learning from sparsely annotated data for semantic segmentation in histopathology images. MIDL 2019: 84-91 - [c19]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 - [i10]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) - [i9]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) - 2018
- [j6]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) - [c18]Farhad Ghazvinian Zanjani, Svitlana Zinger, Babak Ehteshami Bejnordi, Jeroen A. W. M. van der Laak, Peter H. N. de With:
Stain normalization of histopathology images using generative adversarial networks. ISBI 2018: 573-577 - [c17]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 - [c16]John-Melle Bokhorst, Lucia Rijstenberg, Danny Goudkade, Iris Nagtegaal, Jeroen van der Laak, Francesco Ciompi:
Automatic Detection of Tumor Budding in Colorectal Carcinoma with Deep Learning. COMPAY/OMIA@MICCAI 2018: 130-138 - [c15]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. Medical Imaging: Digital Pathology 2018: 105810S - [c14]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. Medical Imaging: Digital Pathology 2018: 105810L - [c13]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. Medical Imaging: Digital Pathology 2018: 105810Z - [c12]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. Medical Imaging: Digital Pathology 2018: 1058112 - [e1]Danail Stoyanov, Zeike Taylor, Francesco Ciompi, Yanwu Xu, Anne L. Martel, Lena Maier-Hein, Nasir M. Rajpoot, Jeroen van der Laak, Mitko Veta, Stephen J. McKenna, David R. J. Snead, Emanuele Trucco, Mona Kathryn Garvin, Xinjian Chen, Hrvoje Bogunovic:
Computational Pathology and Ophthalmic Medical Image Analysis - First International Workshop, COMPAY 2018, and 5th International Workshop, OMIA 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings. Lecture Notes in Computer Science 11039, Springer 2018, ISBN 978-3-030-00948-9 [contents] - [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
- [j5]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) - [j4]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) - [c11]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 - [c10]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 - [c9]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck:
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. ISBI 2017: 929-932 - [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]Babak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, Maeve Mullooly, Gretchen L. Gierach, Mark E. Sherman, Nico Karssemeijer, Jeroen van der Laak, Andrew H. Beck:
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images. CoRR abs/1702.05803 (2017) - [i3]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) - [i2]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) - [i1]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
- [j3]Bonnie Nijhof, Anna Castells-Nobau, Louis Wolf, Jolanda M. Scheffer-de Gooyert, Ignacio Monedero, Laura Torroja, Lluís Coromina, Jeroen A. W. M. van der Laak, Annette Schenck:
A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry. PLoS Comput. Biol. 12(3) (2016) - [j2]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) - [j1]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) - [c8]Melih Kandemir, Manuel Haußmann, Ferran Diego, Kumar T. Rajamani, Jeroen van der Laak, Fred A. Hamprecht:
Variational Weakly Supervised Gaussian Processes. BMVC 2016 - [c7]Thomy Mertzanidou, John H. Hipwell, Sara Reis, Babak Ehteshami Bejnordi, Meyke Hermsen, Mehmet Dalmis, Suzan Vreemann, Bram Platel, Jeroen van der Laak, Nico Karssemeijer, Ritse Mann, Peter Bult, David J. Hawkes:
Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology. Digital Mammography / IWDM 2016: 367-374 - [c6]Henning Kost, André Homeyer, Peter Bult, Maschenka C. A. Balkenhol, Jeroen A. W. M. van der Laak, Horst K. Hahn:
A generic nuclei detection method for histopathological breast images. Medical Imaging: Digital Pathology 2016: 97911E - 2015
- [c5]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. Medical Imaging: Digital Pathology 2015: 94200H - [c4]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. Medical Imaging: Digital Pathology 2015: 94200B - [c3]Sara Reis, Björn Eiben, Thomy Mertzanidou, John H. Hipwell, Meyke Hermsen, Jeroen van der Laak, Sarah E. Pinder, Peter Bult, David J. Hawkes:
Minimum slice spacing required to reconstruct 3D shape for serial sections of breast tissue for comparison with medical imaging. Medical Imaging: Digital Pathology 2015: 94200K - 2014
- [c2]Thomy Mertzanidou, John H. Hipwell, Mehmet Dalmis, Bram Platel, Jeroen van der Laak, Ritse Mann, Nico Karssemeijer, Peter Bult, David J. Hawkes:
Towards Spatial Correspondence between Specimen and In-vivo Breast Imaging. Digital Mammography / IWDM 2014: 674-680 - [c1]Babak Ehteshami Bejnordi, Nadya Timofeeva, Irene Otte-Höller, Nico Karssemeijer, Jeroen A. W. M. van der Laak:
Quantitative analysis of stain variability in histology slides and an algorithm for standardization. Medical Imaging: Digital Pathology 2014: 904108
Coauthor Index
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