Search Results - "van Rijthoven, Mart"

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations by Marini, Niccolò, Marchesin, Stefano, Otálora, Sebastian, Wodzinski, Marek, Caputo, Alessandro, van Rijthoven, Mart, Aswolinskiy, Witali, Bokhorst, John-Melle, Podareanu, Damian, Petters, Edyta, Boytcheva, Svetla, Buttafuoco, Genziana, Vatrano, Simona, Fraggetta, Filippo, van der Laak, Jeroen, Agosti, Maristella, Ciompi, Francesco, Silvello, Gianmaria, Muller, Henning, Atzori, Manfredo

“…The digitalization of clinical workflows and the increasing performance of deep learning algorithms are paving the way towards new methods for tackling cancer…”
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Multi-resolution deep learning characterizes tertiary lymphoid structures and their prognostic relevance in solid tumors by van Rijthoven, Mart, Obahor, Simon, Pagliarulo, Fabio, van den Broek, Maries, Schraml, Peter, Moch, Holger, van der Laak, Jeroen, Ciompi, Francesco, Silina, Karina

“…Background Tertiary lymphoid structures (TLSs) are dense accumulations of lymphocytes in inflamed peripheral tissues, including cancer, and are associated with…”
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Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images by Marini, Niccolò, Otálora, Sebastian, Podareanu, Damian, van Rijthoven, Mart, van der Laak, Jeroen, Ciompi, Francesco, Müller, Henning, Atzori, Manfredo

“…Algorithms proposed in computational pathology can allow to automatically analyze digitized tissue samples of histopathological images to help diagnosing…”
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HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images by van Rijthoven, Mart, Balkenhol, Maschenka, Siliņa, Karina, van der Laak, Jeroen, Ciompi, Francesco

“…•HookNet: a multi-resolution semantic segmentation framework that combines context and details via encoder-decoder branches.•The model is applied for breast…”
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Learning to detect lymphocytes in immunohistochemistry with deep learning by Swiderska-Chadaj, Zaneta, Pinckaers, Hans, van Rijthoven, Mart, Balkenhol, Maschenka, Melnikova, Margarita, Geessink, Oscar, Manson, Quirine, Sherman, Mark, Polonia, Antonio, Parry, Jeremy, Abubakar, Mustapha, Litjens, Geert, van der Laak, Jeroen, Ciompi, Francesco

“…•Deep learning approaches can be applied for automatic detection of lymphocytes in immunohistochemically stained tissue sections.•An observer study on…”
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HookNet: multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images by van Rijthoven, Mart, Balkenhol, Maschenka, Siliņa, Karina, van der Laak, Jeroen, Ciompi, Francesco

“…We propose HookNet, a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of…”
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