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1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset
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1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset

Litjens, Geert ; Bandi, Peter ; Ehteshami Bejnordi, Babak ; Geessink, Oscar ; Balkenhol, Maschenka ; Bult, Peter ; Halilovic, Altuna ; Hermsen, Meyke ; van de Loo, Rob ; Vogels, Rob ; Manson, Quirine F ; Stathonikos, Nikolas ; Baidoshvili, Alexi ; van Diest, Paul ; Wauters, Carla ; van Dijk, Marcory ; van der Laak, Jeroen

Gigascience, 2018-06, Vol.7 (6) [Periódico revisado por pares]

Oxford University Press

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2
A survey on deep learning in medical image analysis
A survey on deep learning in medical image analysis
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A survey on deep learning in medical image analysis

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.

Medical image analysis, 2017-12, Vol.42, p.60-88 [Periódico revisado por pares]

Netherlands: Elsevier B.V

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3
Stain Specific Standardization of Whole-Slide Histopathological Images
Stain Specific Standardization of Whole-Slide Histopathological Images
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Stain Specific Standardization of Whole-Slide Histopathological Images

Ehteshami Bejnordi, Babak ; Litjens, Geert ; Timofeeva, Nadya ; Otte-Holler, Irene ; Homeyer, Andre ; Karssemeijer, Nico ; van der Laak, Jeroen Awm

IEEE transactions on medical imaging, 2016-02, Vol.35 (2), p.404-415

United States: IEEE

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4
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies
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Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies

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.

Modern pathology, 2018-10, Vol.31 (10), p.1502-1512 [Periódico revisado por pares]

United States: Elsevier Inc

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5
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images
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Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images

Ehteshami Bejnordi, Babak ; Balkenhol, Maschenka ; Litjens, Geert ; Holland, Roland ; Bult, Peter ; Karssemeijer, Nico ; van der Laak, Jeroen A. W. M.

IEEE transactions on medical imaging, 2016-09, Vol.35 (9), p.2141-2150

United States: IEEE

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6
Deep learning assisted mitotic counting for breast cancer
Deep learning assisted mitotic counting for breast cancer
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Deep learning assisted mitotic counting for breast cancer

Balkenhol, Maschenka C.A. ; Tellez, David ; Vreuls, Willem ; Clahsen, Pieter C. ; Pinckaers, Hans ; Ciompi, Francesco ; Bult, Peter ; van der Laak, Jeroen A.W.M.

Laboratory investigation, 2019-11, Vol.99 (11), p.1596-1606 [Periódico revisado por pares]

United States: Elsevier Inc

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7
Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning
Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning
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Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning

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.

Laboratory investigation, 2021-08, Vol.101 (8), p.970-982 [Periódico revisado por pares]

United States: Elsevier Inc

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8
Deep learning in histopathology: the path to the clinic
Deep learning in histopathology: the path to the clinic
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Deep learning in histopathology: the path to the clinic

van der Laak, Jeroen ; Litjens, Geert ; Ciompi, Francesco

Nature medicine, 2021-05, Vol.27 (5), p.775-784 [Periódico revisado por pares]

United States: Nature Publishing Group

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9
Pathologists’ first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study
Pathologists’ first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study
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Pathologists’ first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study

Swillens, Julie E. M. ; Nagtegaal, Iris D. ; Engels, Sam ; Lugli, Alessandro ; Hermens, Rosella P. M. G. ; van der Laak, Jeroen A. W. M.

Oncogene, 2023-09, Vol.42 (38), p.2816-2827 [Periódico revisado por pares]

New York: Nature Publishing Group

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10
Deep Learning-Based Histopathologic Assessment of Kidney Tissue
Deep Learning-Based Histopathologic Assessment of Kidney Tissue
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Deep Learning-Based Histopathologic Assessment of Kidney Tissue

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

Journal of the American Society of Nephrology, 2019-10, Vol.30 (10), p.1968-1979 [Periódico revisado por pares]

United States: American Society of Nephrology

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