Babak Ehteshami Bejnordi

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Jeroen van der LaakRadboud University Medical CenterDirección de correo verificada de radboudumc.nl
Geert LitjensRadboud University Medical CenterDirección de correo verificada de radboudumc.nl
Bram van GinnekenProfessor of Medical Image Analysis, Radboud UniversityDirección de correo verificada de radboudumc.nl
Mohsen GhafoorianSr. Staff Computer Vision R&D, QualcommDirección de correo verificada de qti.qualcomm.com
Nico KarssemeijerProfessor of Computer Aided Diagnosis, Radboud University NijmegenDirección de correo verificada de radboudumc.nl
Tijmen BlankevoortMeta Reality LabsDirección de correo verificada de qti.qualcomm.com
Amirhossein HabibianResearch Scientist, Qualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com
Andrew H. BeckCo-Founder and CEO at PathAIDirección de correo verificada de PathAI.com
Jakub M. TomczakAssociate professor at Eindhoven University of TechnologyDirección de correo verificada de tue.nl
Amir GhodratiQualcomm AI Research NetherlandsDirección de correo verificada de qti.qualcomm.com
Max WellingCAIO CuspAI & Professor Machine Learning, University of AmsterdamDirección de correo verificada de uva.nl
Amélie RoyerStaff Engineer, Qualcomm AI Research NetherlandsDirección de correo verificada de ist.ac.at
Taco CohenQualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com
Andrew MehnertLions Eye InstituteDirección de correo verificada de lei.org.au
Fatih PorikliQualcomm, Australian National UniversityDirección de correo verificada de anu.edu.au
Mahdi S. HosseiniAssistant Professor, Concordia University and Mila Quebec AI InstituteDirección de correo verificada de concordia.ca
Jonas TeuwenNetherlands Cancer Institute / Radboud University Medical CenterDirección de correo verificada de nki.nl
Radu TimofteHumboldt Professor for AI and Computer Vision, University of WürzburgDirección de correo verificada de uni-wuerzburg.de
Luc Van Goolprofessor computer vision INSAIT Sofia University, em. KU Leuven, em. ETHZ, Toyota Lab TRACEDirección de correo verificada de insait.ai
Christos LouizosQualcomm AI ResearchDirección de correo verificada de qti.qualcomm.com

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Babak Ehteshami Bejnordi

Sr. Staff Research Scientist, Qualcomm AI Research

Dirección de correo verificada de qti.qualcomm.com - Página principal

Efficient AI LLM Computer Vision Machine Learning Medical Imaging


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	13370	2017
Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer BE Bejnordi, M Veta, PJ Van Diest, B Van Ginneken, N Karssemeijer, ... Jama 318 (22), 2199-2210, 2017	3251	2017
From detection of individual metastases to classification of lymph node status at the patient level: the camelyon17 challenge P Bandi, O Geessink, Q Manson, M Van Dijk, M Balkenhol, M Hermsen, ... IEEE transactions on medical imaging 38 (2), 550-560, 2018	611	2018
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset G Litjens, P Bandi, B Ehteshami Bejnordi, O Geessink, M Balkenhol, ... GigaScience 7 (6), giy065, 2018	402	2018
Stain specific standardization of whole-slide histopathological images BE Bejnordi, G Litjens, N Timofeeva, I Otte-Höller, A Homeyer, ... IEEE transactions on medical imaging 35 (2), 404-415, 2015	327	2015
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	312	2019
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	237	2017
Conditional channel gated networks for task-aware continual learning D Abati, J Tomczak, T Blankevoort, S Calderara, R Cucchiara, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020	227	2020
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images BE Bejnordi, G Zuidhof, M Balkenhol, M Hermsen, P Bult, B van Ginneken, ... Journal of Medical Imaging 4 (4), 044504-044504, 2017	222	2017
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies B Ehteshami Bejnordi, M Mullooly, RM Pfeiffer, S Fan, PM Vacek, ... Modern Pathology 31 (10), 1502-1512, 2018	213	2018
Stain normalization of histopathology images using generative adversarial networks FG Zanjani, S Zinger, BE Bejnordi, JAWM van der Laak, PHN de With 2018 IEEE 15th International symposium on biomedical imaging (ISBI 2018 …, 2018	149	2018
Automated detection of DCIS in whole-slide H&E stained breast histopathology images BE Bejnordi, M Balkenhol, G Litjens, R Holland, P Bult, N Karssemeijer, ... IEEE transactions on medical imaging 35 (9), 2141-2150, 2016	112	2016
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, 331-341, 2019	104	2019
Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images BE Bejnordi, J Lin, B Glass, M Mullooly, GL Gierach, ME Sherman, ... 2017 IEEE 14th international symposium on biomedical imaging (ISBI 2017 …, 2017	97	2017
Batch-Shaping for Learning Conditional Channel Gated Networks B Ehteshami Bejnordi, T Blankevoort, M Welling Proceedings of the eights International Conference on Learning …, 2020	87*	2020
Frameexit: Conditional early exiting for efficient video recognition A Ghodrati, BE Bejnordi, A Habibian Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	83	2021
A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images BE Bejnordi, G Litjens, M Hermsen, N Karssemeijer, JAWM van der Laak Medical Imaging 2015: Digital Pathology 9420, 99-104, 2015	62	2015
Skip-convolutions for efficient video processing A Habibian, D Abati, TS Cohen, BE Bejnordi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021	60	2021
Quantitative analysis of stain variability in histology slides and an algorithm for standardization BE Bejnordi, N Timofeeva, I Otte-Höller, N Karssemeijer, ... Medical Imaging 2014: Digital Pathology 9041, 45-51, 2014	57	2014
Histopathology stain-color normalization using deep generative models FG Zanjani, S Zinger, BE Bejnordi, JAWM van der Laak 1st Conference on Medical Imaging with Deep Learning (MIDL 2018), 1-11, 2018	55	2018

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