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Sebastian Krappe
Sebastian Krappe
Siemens Healthineers
Verified email at siemens-healthineers.com
Title
Cited by
Cited by
Year
Highly accurate differentiation of bone marrow cell morphologies using deep neural networks on a large image data set
C Matek, S Krappe, C Münzenmayer, T Haferlach, C Marr
Blood, The Journal of the American Society of Hematology 138 (20), 1917-1927, 2021
972021
Automatic classification of minimally invasive instruments based on endoscopic image sequences
S Speidel, J Benzko, S Krappe, G Sudra, P Azad, BP Müller-Stich, C Gutt, ...
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling …, 2009
532009
Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical …
S Krappe, T Wittenberg, T Haferlach, C Münzenmayer
SPIE Medical Imaging 2016: Computer-Aided Diagnosis, 2016
152016
Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality
S Krappe, M Benz, T Wittenberg, T Haferlach, T Münzenmayer
SPIE Medical Imaging 2015, 2015
112015
Robust feature tracking for endoscopic pose estimation and structure recovery
S Speidel, S Krappe, S Röhl, S Bodenstedt, B Müller-Stich, R Dillmann
SPIE Medical Imaging, 2013
82013
An expert-annotated dataset of bone marrow cytology in hematologic malignancies
C Matek, S Krappe, C Münzenmayer, T Haferlach, C Marr
The Cancer Imaging Archive, 2021
62021
Lokalisierung von Knochenmarkzellen für die automatisierte morphologische Analyse von Knochenmarkpräparaten
S Krappe, K Macijewski, E Eismann, T Ziegler, T Wittenberg, T Haferlach, ...
Bildverarbeitung für die Medizin 2014: Algorithmen-Systeme-Anwendungen …, 2014
62014
Automated cancer stem cell recognition in H and E stained tissue using convolutional neural networks and color deconvolution
W Aichinger, S Krappe, AE Cetin, R Cetin-Atalay, A Üner, M Benz, ...
Medical Imaging 2017: Digital Pathology 10140, 159-164, 2017
52017
Automated plasmodia recognition in microscopic images for diagnosis of malaria using convolutional neural networks
S Krappe, M Benz, A Gryanik, E Tannich, C Wegner, M Stamminger, ...
Medical Imaging 2017: Digital Pathology 10140, 67-72, 2017
42017
Dynamic programming for the segmentation of bone marrow cells
S Krappe, C Münzenmayer, A Evert, CF Koyuncu, E Cetin, T Haferlach, ...
Bildverarbeitung für die Medizin 2015: Algorithmen-Systeme-Anwendungen …, 2015
32015
Training und Qualitätssicherung für die morphologische Analyse von Knochenmarkpräparaten
S Krappe, E Efstathiou, T Haferlach, K Macijewski, T Wittenberg, ...
22013
Automatische Klassifikation von hämatopoetischen Zellen für ein computer-assistiertes Mikroskopiesystem
S Krappe
12018
A Database and Neural Network for Highly Accurate Classification of Single Bone Marrow Cells
C Matek, S Krappe, C Münzenmayer, T Haferlach, C Marr
Bildverarbeitung für die Medizin 2022: Proceedings, German Workshop on …, 2022
2022
Automatic Detection of Relevant Regions for the Morphological Analysis of Bone Marrow Slides
S Krappe, R Leisering, T Haferlach, T Wittenberg, C Münzenmayer
Bildverarbeitung für die Medizin 2016, 272-276, 2016
2016
Track Q. Education and Training for Engineers and Physicians
S Krappe, Y Sahin, T Bindl, T Wittenberg, C Münzenmayer
Biomedical Engineering/Biomedizinische Technik 60 (s1), s361-s366, 2015
2015
An interactive app for training and qualification in differentiating blood cells
S Krappe, Y Sahin, T Bindl, T Wittenberg, C Münzenmayer
Biomed Tech 60 (s1), 2015
2015
Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia
S Krappe, M Benz, T Wittenberg, T Haferlach, C Münzenmayer
2015
Meeting Abstract
S Krappe, E Efstathiou, T Haferlach, K Macijewski, T Wittenberg, ...
2013
GMDS 2013: 58. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V.(GMDS)
S Krappe, E Efstathiou, T Haferlach, K Macijewski, T Wittenberg, ...
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Articles 1–19