Learning to detect lymphocytes in immunohistochemistry with deep learning. - Zaneta Swiderska-Chadaj; Hans Pinckaers; Mart van Rijthoven; Maschenka Balkenhol; Margarita Melnikova; Oscar Geessink; Quirine Manson; Mark Sherman 003; António Polónia; Jeremy Parry; Mustapha Abubakar; Geert Litjens 001; et al. (Medical Image Anal., 2019)

Few-shot weakly supervised detection and retrieval in histopathology whole-slide images. - Mart van Rijthoven; Maschenka Balkenhol; Manfredo Atzori; Peter Bult; Jeroen van der Laak; Francesco Ciompi (Digital Pathology, 2021)

Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images. - Niccolò Marini; Sebastian Otálora; Damian Podareanu; Mart van Rijthoven; Jeroen van der Laak; Francesco Ciompi; Henning Müller; Manfredo Atzori (Frontiers Comput. Sci., 2021)

HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images. - Mart van Rijthoven; Maschenka Balkenhol; Karina Silina; Jeroen van der Laak; Francesco Ciompi (Medical Image Anal., 2021)

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations. - Niccolò Marini; Stefano Marchesin 001; Sebastian Otálora; Marek Wodzinski; Alessandro Caputo; Mart van Rijthoven; Witali Aswolinskiy; John-Melle Bokhorst; Damian Podareanu; Edyta Petters; Svetla Boytcheva; Genziana Buttafuoco; et al. (npj Digit. Medicine, 2022)

nnUNet meets pathology: Bridging the gap for application to whole slide images and computational biomarkers. - 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 (MIDL, 2023)