Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Oscar Geessink"'
Autor:
Jörg Franke, Keisuke Fukuta, Hao Chen, Willem Vreuls, Aoxiao Zhong, Farhad Ghazvinian Zanjani, Svitlana Zinger, Richard J. Chen, Hunter Jackson, Fabian Both, Heidi V.N. Küsters-Vandevelde, Daisuke Komura, Babak Ehteshami Bejnordi, Marcory C. R. F. van Dijk, Bram van Ginneken, Eren Halici, Ludwig Jacobsson, Vlado Ovtcharov, Quanzheng Li, Jeroen van der Laak, Peter Bult, Oscar Geessink, Melih cetin, Shaoqun Zeng, Geert Litjens, Martin Hedlund, Anders Bjorholm Dahl, Byungjae Lee, Péter Bándi, Huangjing Lin, Jeppe Thagaard, Quirine F. Manson, Meyke Hermsen, Shenghua Cheng, Kyunghyun Paeng, Maschenka Balkenhol
Publikováno v:
Bandi, P, Geessink, O, Manson, Q, van Dijk, M, Balkenhol, M, Hermsen, M, Bejnordi, B E, Lee, B, Paeng, K, Zhong, A, Li, Q, Zanjani, F G, Zinger, S, Fukuta, K, Komura, D, Ovtcharov, V, Cheng, S, Zeng, S, Thagaard, J, Dahl, A B, Lin, H, Chen, H, Jacobsson, L, Hedlund, M, Cetin, M, Halici, E, Jackson, H, Chen, R, Both, F, Franke, J, Kusters-Vandevelde, H, Vreuls, W, Bult, P, van Ginneken, B, van der Laak, J & Litjens, G 2018, ' From detection of individual metastases to classification of lymph node status at the patient level: the CAMELYON17 challenge ', I E E E Transactions on Medical Imaging, vol. 38, no. 2, pp. 550-560 . https://doi.org/10.1109/TMI.2018.2867350
IEEE Transactions on Medical Imaging, 38, 2, pp. 550-560
IEEE Transactions on Medical Imaging, 38, 550-560
IEEE Transactions on Medical Imaging, 38(2):8447230, 550-560. Institute of Electrical and Electronics Engineers
IEEE Transactions on Medical Imaging, 38, 2, pp. 550-560
IEEE Transactions on Medical Imaging, 38, 550-560
IEEE Transactions on Medical Imaging, 38(2):8447230, 550-560. Institute of Electrical and Electronics Engineers
Automated detection of cancer metastases in lymph nodes has the potential to improve the assessment of prognosis for patients. To enable fair comparison between the algorithms for this purpose, we set up the CAMELYON17 challenge in conjunction with t
Autor:
Gabi W. van Pelt, Babak Ehteshami Bejnordi, Joost M. Klaase, Francesco Ciompi, Oscar Geessink, Iris D. Nagtegaal, Jeroen van der Laak, Alexi Baidoshvili, Geert Litjens, Wilma E. Mesker
Publikováno v:
Cellular Oncology, 42(3), 331-341
Cellular Oncology, 42, 331-341
Cellular Oncology, 42, 3, pp. 331-341
Cellular Oncology, 42, 331-341
Cellular Oncology, 42, 3, pp. 331-341
Contains fulltext : 204300.pdf (Publisher’s version ) (Open Access) PURPOSE: Tumor-stroma ratio (TSR) serves as an independent prognostic factor in colorectal cancer and other solid malignancies. The recent introduction of digital pathology in rout
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a5006ecaf73082ff6d6a365d72d0411c
http://hdl.handle.net/1887/120073
http://hdl.handle.net/1887/120073
Autor:
Geert Litjens, Mustapha Abubakar, Hans Pinckaers, Margarita Melnikova, Mart van Rijthoven, Oscar Geessink, Quirine F. Manson, Maschenka Balkenhol, Zaneta Swiderska-Chadaj, Jeroen van der Laak, Francesco Ciompi, Jeremy Parry, Mark E. Sherman, António Polónia
Publikováno v:
Medical Image Analysis, 58
Swiderska-Chadaj, Z, Pinckaers, H, van Rijthoven, M, Balkenhol, M, Melnikova, M, Geessink, O, Manson, Q, Sherman, M, Polonia, A, Parry, J, Abubakar, M, Litjens, G, van der Laak, J & Ciompi, F 2019, ' Learning to detect lymphocytes in immunohistochemistry with deep learning ', Medical Image Analysis, vol. 58, 101547 . https://doi.org/10.1016/j.media.2019.101547
Medical Image Analysis
Swiderska-Chadaj, Z, Pinckaers, H, van Rijthoven, M, Balkenhol, M, Melnikova, M, Geessink, O, Manson, Q, Sherman, M, Polonia, A, Parry, J, Abubakar, M, Litjens, G, van der Laak, J & Ciompi, F 2019, ' Learning to detect lymphocytes in immunohistochemistry with deep learning ', Medical Image Analysis, vol. 58, 101547 . https://doi.org/10.1016/j.media.2019.101547
Medical Image Analysis
The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallmarks of cancer. We have built a dataset of 171,166 manually annotated CD3 + and CD8 + cells, which w
Autor:
Jeroen van der Laak, Marcory C. R. F. van Dijk, Oscar Geessink, Paul J. van Diest, Maschenka Balkenhol, Péter Bándi, Nikolas Stathonikos, Rob Vogels, Babak Ehteshami Bejnordi, Meyke Hermsen, Alexi Baidoshvili, Altuna Halilovic, Rob van de Loo, Quirine F. Manson, Geert Litjens, Carla Wauters, Peter Bult
Publikováno v:
Gigascience, 7
GigaScience
Gigascience, 7, 6
GigaScience
Gigascience, 7, 6
Contains fulltext : 193420.pdf (Publisher’s version ) (Open Access) Background: The presence of lymph node metastases is one of the most important factors in breast cancer prognosis. The most common way to assess regional lymph node status is the s
Autor:
Ugur Halici, Rishab Gargeya, Quincy Wong, Hady Ahmady Phoulady, David Tellez, Bram van Ginneken, Andrew H. Beck, Nico Karssemeijer, Jeroen van der Laak, Nassir Navab, Jonas Annuscheit, Leena Latonen, Kaisa Liimatainen, Talha Qaiser, Dayong Wang, Quirine F. Manson, Aoxiao Zhong, Shigeto Seno, Yee-Wah Tsang, Rui Venâncio, Ismael Serrano, Daniel Racoceanu, N. Stathonikos, Muhammad Shaban, Stefanie Demirci, M. Milagro Fernández-Carrobles, Babak Ehteshami Bejnordi, Matt Berseth, Mustafa Umit Oner, Geert Litjens, Kimmo Kartasalo, Hideo Matsuda, Maschenka Balkenhol, Huangjing Lin, Elia Bruni, Hao Chen, Seiryo Watanabe, A. Kalinovsky, Marcory C. R. F. van Dijk, Ami George, Nasir M. Rajpoot, Francisco Beca, Quanzheng Li, Meyke Hermsen, Mira Valkonen, Oscar Deniz, Alexei Vylegzhanin, Vitali Liauchuk, Ruqayya Awan, Mitko Veta, Korsuk Sirinukunwattana, Gloria Bueno, Peter Hufnagl, Christian Haß, Vassili Kovalev, Vitali Khvatkov, Rengul Cetin-Atalay, Humayun Irshad, Oren Kraus, Qi Dou, Pekka Ruusuvuori, Aditya Khosla, Bharti Mungal, Pheng-Ann Heng, Oscar Geessink, Paul J. van Diest, Shadi Albarqouni, Peter Bult, Yoichi Takenaka
Publikováno v:
JAMA Cardiology
JAMA Cardiology, American Medical Association 2017, 318, ⟨10.1001/jama.2017.14585⟩
Jama : Journal of the American Medical Association, 318, 2199-2210
JAMA Neurology, 318(22), 2199-2210. American Medical Association (AMA)
Jama : Journal of the American Medical Association, 318, 22, pp. 2199-2210
JAMA-The Journal of The American Medical Association, 318(22), 2199. American Medical Association
JAMA Cardiology, American Medical Association 2017, 318, ⟨10.1001/jama.2017.14585⟩
Jama : Journal of the American Medical Association, 318, 2199-2210
JAMA Neurology, 318(22), 2199-2210. American Medical Association (AMA)
Jama : Journal of the American Medical Association, 318, 22, pp. 2199-2210
JAMA-The Journal of The American Medical Association, 318(22), 2199. American Medical Association
IMPORTANCE: Application of deep learning algorithms to whole-slide pathology imagescan potentially improve diagnostic accuracy and efficiency. OBJECTIVE: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c5e2e1ebc60e746d57a0deffa5ee651b
https://hal.archives-ouvertes.fr/hal-03140979/document
https://hal.archives-ouvertes.fr/hal-03140979/document
Autor:
Gabriel Silva de Souza, Babak Ehteshami Bejnordi, Oscar Geessink, Francesco Ciompi, Iris D. Nagtegaal, Geert Litjens, Bram van Ginneken, Jeroen van der Laak, Alexi Baidoshvili
Publikováno v:
ISBI
The development of reliable imaging biomarkers for the analysis of colorectal cancer (CRC) in hematoxylin and eosin (H&E) stained histopathology images requires an accurate and reproducible classification of the main tissue components in the image. I
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a1549fa803377a0d858d6beec7b797b
Autor:
Gerard Freling, Alexi Baidoshvili, Ferdinand van der Heijden, Oscar Geessink, Joost M. Klaase, Cornelis H. Slump
Publikováno v:
Medical Imaging 2015: Digital Pathology
Medical Imaging: Digital Pathology
Medical Imaging: Digital Pathology
Visual estimation of tumor and stroma proportions in microscopy images yields a strong, Tumor-(lymph)Node- Metastasis (TNM) classification-independent predictor for patient survival in colorectal cancer. Therefore, it is also a potent (contra)indicat