Deep learning in histopathology: the path to the clinic von van der Laak, Jeroen, Litjens, Geert, Ciompi, Francesco

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A survey on deep learning in medical image analysis von Litjens, Geert, Kooi, Thijs, Bejnordi, Babak Ehteshami, Setio, Arnaud Arindra Adiyoso, Ciompi, Francesco, Ghafoorian, Mohsen, van der Laak, Jeroen A.W.M., van Ginneken, Bram, Sánchez, Clara I.

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Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies von Ehteshami Bejnordi, Babak, Mullooly, Maeve, Pfeiffer, Ruth M., Fan, Shaoqi, Vacek, Pamela M., Weaver, Donald L., Herschorn, Sally, Brinton, Louise A., van Ginneken, Bram, Karssemeijer, Nico, Beck, Andrew H., Gierach, Gretchen L., van der Laak, Jeroen A. W.M., Sherman, Mark E.

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Stain Specific Standardization of Whole-Slide Histopathological Images von Ehteshami Bejnordi, Babak, Litjens, Geert, Timofeeva, Nadya, Otte-Holler, Irene, Homeyer, Andre, Karssemeijer, Nico, van der Laak, Jeroen Awm

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Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images von Ehteshami Bejnordi, Babak, Balkenhol, Maschenka, Litjens, Geert, Holland, Roland, Bult, Peter, Karssemeijer, Nico, van der Laak, Jeroen A. W. M.

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Deep learning assisted mitotic counting for breast cancer von Balkenhol, Maschenka C.A., Tellez, David, Vreuls, Willem, Clahsen, Pieter C., Pinckaers, Hans, Ciompi, Francesco, Bult, Peter, van der Laak, Jeroen A.W.M.

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Deep Learning-Based Histopathologic Assessment of Kidney Tissue von Hermsen, Meyke, de Bel, Thomas, den Boer, Marjolijn, Steenbergen, Eric J, Kers, Jesper, Florquin, Sandrine, Roelofs, Joris J T H, Stegall, Mark D, Alexander, Mariam P, Smith, Byron H, Smeets, Bart, Hilbrands, Luuk B, van der Laak, Jeroen A W M

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Carotenoid and fatty acid metabolism in light-stressed Dunaliella salina von Lamers, Packo P, van de Laak, Carlien C.W, Kaasenbrood, Petrouchka S, Lorier, Jeroen, Janssen, Marcel, De Vos, Ric C.H, Bino, Raoul J, Wijffels, René H

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Assessment of individual tumor buds using keratin immunohistochemistry: moderate interobserver agreement suggests a role for machine learning von Bokhorst, J. M., Blank, A., Lugli, A., Zlobec, I., Dawson, H., Vieth, M., Rijstenberg, L. L., Brockmoeller, S., Urbanowicz, M., Flejou, J. F., Kirsch, R., Ciompi, F., van der Laak, J. A. W. M., Nagtegaal, I. D.

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Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning von Hermsen, Meyke, Volk, Valery, Bräsen, Jan Hinrich, Geijs, Daan J., Gwinner, Wilfried, Kers, Jesper, Linmans, Jasper, Schaadt, Nadine S., Schmitz, Jessica, Steenbergen, Eric J., Swiderska-Chadaj, Zaneta, Smeets, Bart, Hilbrands, Luuk B., Feuerhake, Friedrich, van der Laak, Jeroen A.W.M.

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Primordial black hole isocurvature modes from non-Gaussianity von van Laak, Raphaël, Young, Sam

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Strategic niche management for biofuels: Analysing past experiments for developing new biofuel policies von van der Laak, W.W.M., Raven, R.P.J.M., Verbong, G.P.J.

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Oxidation of methane to methanol and formaldehyde over Co–ZSM-5 molecular sieves: Tuning the reactivity and selectivity by alkaline and acid treatments of the zeolite ZSM-5 agglome... von Beznis, Nadzeya V., van Laak, Adri N.C., Weckhuysen, Bert M., Bitter, Johannes H.

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Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer von Geessink, Oscar G. F., Baidoshvili, Alexi, Klaase, Joost M., Ehteshami Bejnordi, Babak, Litjens, Geert J. S., van Pelt, Gabi W., Mesker, Wilma E., Nagtegaal, Iris D., Ciompi, Francesco, van der Laak, Jeroen A. W. M.

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Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard von Bulten, Wouter, Bándi, Péter, Hoven, Jeffrey, Loo, Rob van de, Lotz, Johannes, Weiss, Nick, Laak, Jeroen van der, Ginneken, Bram van, Hulsbergen-van de Kaa, Christina, Litjens, Geert

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Pathologists’ first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study von Swillens, Julie E. M., Nagtegaal, Iris D., Engels, Sam, Lugli, Alessandro, Hermens, Rosella P. M. G., van der Laak, Jeroen A. W. M.

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Elaboration and validation of the method for the quantification of the emetic toxin of Bacillus cereus as described in EN-ISO 18465 - Microbiology of the food chain – Quantitative... von in 't Veld, P.H., van der Laak, L.F.J., van Zon, M., Biesta-Peters, E.G.

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A whole‐slide imaging based workflow reduces the reading time of pathologists von Baidoshvili, Alexi, Khacheishvili, Mariam, Laak, Jeroen A. W. M., Diest, Paul J.

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Convolutional Neural Networks for the Evaluation of Chronic and Inflammatory Lesions in Kidney Transplant Biopsies von Hermsen, Meyke, Ciompi, Francesco, Adefidipe, Adeyemi, Denic, Aleksandar, Dendooven, Amélie, Smith, Byron H., van Midden, Dominique, Bräsen, Jan Hinrich, Kers, Jesper, Stegall, Mark D., Bándi, Péter, Nguyen, Tri, Swiderska-Chadaj, Zaneta, Smeets, Bart, Hilbrands, Luuk B., van der Laak, Jeroen A.W.M.

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A New Fiji-Based Algorithm That Systematically Quantifies Nine Synaptic Parameters Provides Insights into Drosophila NMJ Morphometry von Nijhof, Bonnie, Castells-Nobau, Anna, Wolf, Louis, Scheffer-de Gooyert, Jolanda M, Monedero, Ignacio, Torroja, Laura, Coromina, Lluis, van der Laak, Jeroen A W M, Schenck, Annette

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