Francesco Ciompi

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Jeroen van der LaakRadboud University Medical CenterDirección de correo verificada de radboudumc.nl
Bram van GinnekenProfessor of Medical Image Analysis, Radboud UniversityDirección de correo verificada de radboudumc.nl
Geert LitjensRadboud University Medical CenterDirección de correo verificada de radboudumc.nl
petia radevaFull professor, University of Barcelona, Senior Researcher, Computer Vision CenterDirección de correo verificada de ub.edu
Arnaud Arindra Adiyoso SetioSiemens HealthineersDirección de correo verificada de siemens-healthineers.com
Colin JacobsRadboudumc, Nijmegen, The NetherlandsDirección de correo verificada de radboudumc.nl
Oriol PujolFull Professor of Computer Science and Artificial Intelligence, Universitat de BarcelonaDirección de correo verificada de ub.edu
Mathias ProkopProfessor of Radiology, RadboudumcDirección de correo verificada de radboudumc.nl
Babak Ehteshami BejnordiResearch Scientist, Qualcomm AI Research, Qualcomm Technologies, Inc., NetherlandsDirección de correo verificada de qti.qualcomm.com
David TellezPhD student, Department of Pathology, RadboudumcDirección de correo verificada de radboudumc.nl
Maschenka Balkenhol MD, PhDPathology Resident & Researcher, Computational Pathology, RadboudumcDirección de correo verificada de radboudumc.nl
Clara I. SánchezFull Professor, Informatics Institute, University of AmsterdamDirección de correo verificada de uva.nl
Iris NagtegaalDirección de correo verificada de radboudumc.nl
J-M BokhorstPhD student, Radboud university medical centerDirección de correo verificada de radboudumc.nl
Kaman ChungDirección de correo verificada de radboudumc.nl
Thijs KooiLunit Inc.Dirección de correo verificada de lunit.io
Mohsen GhafoorianMachine Learning R&D, QualcommDirección de correo verificada de qti.qualcomm.com
Mart van RijthovenPhD Candidate, Deep learning & Computational Pathology, Radboud University Medical CenterDirección de correo verificada de radboudumc.nl
Oscar GeessinkPhD candidate, Dept. of Pathology, Radboud University Medical CenterDirección de correo verificada de radboudumc.nl
Pim de JongUMC UtrechtDirección de correo verificada de umcutrecht.nl

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Francesco Ciompi

Radboud University Medical Center, Nijmegen

Dirección de correo verificada de radboudumc.nl - Página principal

Deep Learning Computational Pathology Medical Image Analysis Computer Aided Diagnosis


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
A survey on deep learning in medical image analysis G Litjens, T Kooi, BE Bejnordi, AAA Setio, F Ciompi, M Ghafoorian, ... Medical image analysis 42, 60-88, 2017	8205	2017
Pulmonary nodule detection in CT images: false positive reduction using multi-view convolutional networks AAA Setio, F Ciompi, G Litjens, P Gerke, C Jacobs, SJ Van Riel, ... IEEE transactions on medical imaging 35 (5), 1160-1169, 2016	1033	2016
Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans B Van Ginneken, AAA Setio, C Jacobs, F Ciompi 2015 IEEE 12th International symposium on biomedical imaging (ISBI), 286-289, 2015	317	2015
Towards automatic pulmonary nodule management in lung cancer screening with deep learning F Ciompi, K Chung, SJ Van Riel, AAA Setio, PK Gerke, C Jacobs, ... Scientific reports 7 (1), 1-11, 2017	307	2017
Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box F Ciompi, B de Hoop, SJ van Riel, K Chung, ET Scholten, M Oudkerk, ... Medical image analysis 26 (1), 195-202, 2015	292	2015
Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology D Tellez, G Litjens, P Bándi, W Bulten, JM Bokhorst, F Ciompi, ... Medical image analysis 58, 101544, 2019	220	2019
State-of-the-art deep learning in cardiovascular image analysis G Litjens, F Ciompi, JM Wolterink, BD de Vos, T Leiner, J Teuwen, I Išgum JACC: Cardiovascular imaging 12 (8 Part 1), 1549-1565, 2019	176	2019
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ... Medical image analysis 54, 111-121, 2019	171	2019
Whole-slide mitosis detection in H&E breast histology using PHH3 as a reference to train distilled stain-invariant convolutional networks D Tellez, M Balkenhol, I Otte-Höller, R van de Loo, R Vogels, P Bult, ... IEEE transactions on medical imaging 37 (9), 2126-2136, 2018	157	2018
The importance of stain normalization in colorectal tissue classification with convolutional networks F Ciompi, O Geessink, BE Bejnordi, GS De Souza, A Baidoshvili, G Litjens, ... 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017	156	2017
Standardized evaluation methodology and reference database for evaluating IVUS image segmentation S Balocco, C Gatta, F Ciompi, A Wahle, P Radeva, S Carlier, G Unal, ... Computerized medical imaging and graphics 38 (2), 70-90, 2014	126	2014
Deep learning in histopathology: the path to the clinic J Van der Laak, G Litjens, F Ciompi Nature medicine 27 (5), 775-784, 2021	111	2021
Neural image compression for gigapixel histopathology image analysis D Tellez, G Litjens, J van der Laak, F Ciompi IEEE transactions on pattern analysis and machine intelligence 43 (2), 567-578, 2019	97	2019
Rayleigh mixture model for plaque characterization in intravascular ultrasound JC Seabra, F Ciompi, O Pujol, J Mauri, P Radeva, J Sanches IEEE Transactions on Biomedical Engineering 58 (5), 1314-1324, 2011	96	2011
Improving airway segmentation in computed tomography using leak detection with convolutional networks JP Charbonnier, EM Van Rikxoort, AAA Setio, CM Schaefer-Prokop, ... Medical image analysis 36, 52-60, 2017	87	2017
Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer Z Kos, E Roblin, RS Kim, S Michiels, BD Gallas, W Chen, KK van de Vijver, ... NPJ breast cancer 6 (1), 1-16, 2020	72	2020
Report on computational assessment of tumor infiltrating lymphocytes from the International Immuno-Oncology Biomarker Working Group M Amgad, ES Stovgaard, E Balslev, J Thagaard, W Chen, S Dudgeon, ... NPJ breast cancer 6 (1), 1-13, 2020	72	2020
Learning to detect lymphocytes in immunohistochemistry with deep learning Z Swiderska-Chadaj, H Pinckaers, M van Rijthoven, M Balkenhol, ... Medical image analysis 58, 101547, 2019	70	2019
HoliMAb: A holistic approach for Media–Adventitia border detection in intravascular ultrasound F Ciompi, O Pujol, C Gatta, M Alberti, S Balocco, X Carrillo, J Mauri-Ferre, ... Medical image analysis 16 (6), 1085-1100, 2012	62	2012
Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer OGF Geessink, A Baidoshvili, JM Klaase, B Ehteshami Bejnordi, ... Cellular oncology 42 (3), 331-341, 2019	56	2019

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