Nico Karssemeijer - Concepedia

Author

Nico Karssemeijer

Also Known As

Karssemeijer Nico, Karssemeijer, N., Karssemeijer, Nico, M Imhof-Tas, M. Imhof-Tas, N Karssemeijer, N. Karssemeijer, NICO KARSSEMEIJER, Nico Karssemeijer, Nico Karssemeijer (511568)

281

Publications

16.3K

Citations

H-Index

127

Concepts

All Affiliations

Radboud University Nijmegen Radboud University Medical Center University Medical Center Utrecht Dutch Expert Centre for Screening University Medical Center

About

Nico Karssemeijer is an author at Radboud University Nijmegen specializing in radiology, medical imaging, and engineering.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	39	66	5.5K
2	Health Sciences	27	39	3.7K
3	Medicine	23	30	2.3K
4	Natural Sciences	3	3	114
5	Public Health	1	1	70

Nico Karssemeijer

144

Publications

14.8K

Citations

H-Index

Page 1

	Year	Citations
Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer Babak Ehteshami Bejnordi, Mitko Veta, Paul Johannes van Diest, JAMA	2017	3.2K
Large scale deep learning for computer aided detection of mammographic lesions Thijs Kooi, Geert Litjens, Bram van Ginneken, Medical Image Analysis Dermoscopic ImageConvolutional Neural NetworkImage AnalysisMachine LearningData Science	2016	951
Supplemental MRI Screening for Women with Extremely Dense Breast Tissue Marije F. Bakker, Stéphanie V. de Lange, Ruud M. Pijnappel, New England Journal of Medicine	2019	655
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring Michiel Kallenberg, Kersten Petersen, Mads Nielsen, IEEE Transactions on Medical Imaging Convolutional Neural NetworkMultiple Instance LearningEngineeringMachine LearningImage Analysis	2016	437
Stain Specific Standardization of Whole-Slide Histopathological Images Babak Ehteshami Bejnordi, Geert Litjens, N. K. Timofeeva, IEEE Transactions on Medical Imaging Stain NormalizationWhole-slide ImagingDigital PathologyHistologyPathology	2015	285
Automated classification of parenchymal patterns in mammograms Nico Karssemeijer Physics in Medicine and Biology EngineeringBiometricsDigital PathologyDiagnostic ImagingParenchymal Patterns	1998	276
Detection of stellate distortions in mammograms Nico Karssemeijer, G.M. te Brake IEEE Transactions on Medical Imaging EngineeringStellate DistortionsDiagnostic ImagingImage AnalysisPattern Recognition	1996	256
Volumetric breast density estimation from full-field digital mammograms Saskia van Engeland, Peter R. Snoeren, Henkjan Huisman, IEEE Transactions on Medical Imaging EngineeringMeasurementBiomedical EngineeringDiagnostic ImagingDense Tissue Mapping	2006	234
A Novel Approach to Contrast-Enhanced Breast Magnetic Resonance Imaging for Screening Ritse M. Mann, Roel Mus, Jan van Zelst, Investigative Radiology	2014	216
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies Babak Ehteshami Bejnordi, Maeve Mullooly, Ruth M. Pfeiffer, Modern Pathology EngineeringMachine LearningDeep LearningMedical ImagingCancer Detection	2018	212

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