Publications of Mart van Rijthoven
Papers in international journals
- M. van Rijthoven, S. Obahor, F. Pagliarulo, V. den Maries, P. Schraml, H. Moch, J. van der Laak, F. Ciompi and K. Silina, "Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors", Communications Medicine, 2024.
- N. Marini, S. Marchesin, S. Otalora, M. Wodzinski, A. Caputo, M. van Rijthoven, W. Aswolinskiy, J. Bokhorst, D. Podareanu, E. Petters, S. Boytcheva, G. Buttafuoco, S. Vatrano, F. Fraggetta, J. van der Laak, M. Agosti, F. Ciompi, G. Silvello, H. Muller and M. Atzori, "Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations.", NPJ digital medicine, 2022;5(1):102.
- M. van Rijthoven, M. Balkenhol, K. Silina, J. van der Laak and F. Ciompi, "HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images", Medical Image Analysis, 2021;68:101890.
- N. Marini, S. Otálora, D. Podareanu, M. van Rijthoven, J. van der Laak, F. Ciompi, H. Muller and M. Atzori, "Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images", Frontiers in Computer Science, 2021;3.
- Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, M. Sherman, A. Polonia, J. Parry, M. Abubakar, G. Litjens, J. van der Laak and F. Ciompi, "Learning to detect lymphocytes in immunohistochemistry with deep learning", Medical Image Analysis, 2019;58:101547.
Papers in conference proceedings
- J. Spronck, T. Gelton, L. van Eekelen, J. Bogaerts, L. Tessier, M. van Rijthoven, L. van der Woude, M. van den Heuvel, W. Theelen, J. van der Laak and F. Ciompi, "nnUNet meets pathology: bridging the gap for application to whole-slide images and computational biomarkers", Medical Imaging with Deep Learning, 2023.
- M. van Rijthoven, M. Balkenhol, M. Atzori, P. Bult, J. van der Laak and F. Ciompi, "Few-shot weakly supervised detection and retrieval in histopathology whole-slide images", Medical Imaging, 2021;11603:137 - 143.
- Z. Swiderska-Chadaj, H. Pinckaers, M. van Rijthoven, M. Balkenhol, M. Melnikova, O. Geessink, Q. Manson, G. Litjens, J. van der Laak and F. Ciompi, "Convolutional Neural Networks for Lymphocyte detection in Immunohistochemically Stained Whole-Slide Images", Medical Imaging with Deep Learning, 2018.
- M. van Rijthoven, Z. Swiderska-Chadaj, K. Seeliger, J. van der Laak and F. Ciompi, "You Only Look on Lymphocytes Once", Medical Imaging with Deep Learning, 2018.
Abstracts
- M. D'Amato, M. Balkenhol, M. van Rijthoven, J. van der Laak and F. Ciompi, "On the robustness of regressing tumor percentage as an explainable detector in histopathology whole-slide images", Medical Imaging with Deep Learning, 2023.
- Y. Jiao, M. Rijthoven, J. Li, K. Grunberg, S. Fei and F. Ciompi, "Automatic Lung Cancer Segmentation in Histopathology Whole-Slide Images with Deep Learning", European Congress on Digital Pathology (ECDP), 2021.
Master theses
- M. van Rijthoven, "Cancer research in digital pathology using convolutional neural networks", Master thesis, 2019.