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Babak Ehteshami Bejnordi

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysisRamin Moshavegh, Babak Ehteshami Bejnordi, Andrew Mehnert, et al.
IEEE Transactions on Medical Imaging|April 15, 2016
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology ImagesBabak Ehteshami Bejnordi, Maschenka Balkenhol, Geert Litjens, et al.
IEEE Transactions on Medical Imaging|September 10, 2015
Stain Specific Standardization of Whole-Slide Histopathological ImagesBabak Ehteshami Bejnordi, Geert Litjens, Nadya Timofeeva, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 30, 2017
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology imagesBabak Ehteshami Bejnordi, Guido Zuidhof, Maschenka Balkenhol, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|October 23, 2019
DEEP LEARNING-BASED ASSESSMENT OF TUMOR-ASSOCIATED STROMA FOR DIAGNOSING BREAST CANCER IN HISTOPATHOLOGY IMAGESBabak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, et al.
Medical Image Analysis|August 5, 2017
A survey on deep learning in medical image analysisGeert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, et al.
Medical Physics|January 9, 2017
3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imagingThomy Mertzanidou, John H Hipwell, Sara Reis, et al.
Cellular Oncology (Dordrecht, Netherlands)|March 3, 2019
Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancerOscar G F Geessink, Alexi Baidoshvili, Joost M Klaase, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|June 15, 2018
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsiesBabak Ehteshami Bejnordi, Maeve Mullooly, Ruth M Pfeiffer, et al.
Gigascience|June 4, 2018
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON datasetGeert Litjens, Peter Bandi, Babak Ehteshami Bejnordi, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

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Pageof 2
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
Automated segmentation of free-lying cell nuclei in Pap smears for malignancy-associated change analysisRamin Moshavegh, Babak Ehteshami Bejnordi, Andrew Mehnert, et al.
IEEE Transactions on Medical Imaging|April 15, 2016
Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology ImagesBabak Ehteshami Bejnordi, Maschenka Balkenhol, Geert Litjens, et al.
IEEE Transactions on Medical Imaging|September 10, 2015
Stain Specific Standardization of Whole-Slide Histopathological ImagesBabak Ehteshami Bejnordi, Geert Litjens, Nadya Timofeeva, et al.
Journal of Medical Imaging (Bellingham, Wash.)|December 30, 2017
Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology imagesBabak Ehteshami Bejnordi, Guido Zuidhof, Maschenka Balkenhol, et al.
Proceedings. IEEE International Symposium on Biomedical Imaging|October 23, 2019
DEEP LEARNING-BASED ASSESSMENT OF TUMOR-ASSOCIATED STROMA FOR DIAGNOSING BREAST CANCER IN HISTOPATHOLOGY IMAGESBabak Ehteshami Bejnordi, Jimmy Lin, Ben Glass, et al.
Medical Image Analysis|August 5, 2017
A survey on deep learning in medical image analysisGeert Litjens, Thijs Kooi, Babak Ehteshami Bejnordi, et al.
Medical Physics|January 9, 2017
3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imagingThomy Mertzanidou, John H Hipwell, Sara Reis, et al.
Cellular Oncology (Dordrecht, Netherlands)|March 3, 2019
Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancerOscar G F Geessink, Alexi Baidoshvili, Joost M Klaase, et al.
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|June 15, 2018
Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsiesBabak Ehteshami Bejnordi, Maeve Mullooly, Ruth M Pfeiffer, et al.
Gigascience|June 4, 2018
1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON datasetGeert Litjens, Peter Bandi, Babak Ehteshami Bejnordi, et al.
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