Sorbonne University, Paris Brain Institute
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Zitiert von
Zitiert von
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
Methods for nuclei detection, segmentation, and classification in digital histopathology: a review—current status and future potential
H Irshad, A Veillard, L Roux, D Racoceanu
IEEE reviews in biomedical engineering 7, 97-114, 2013
Gland segmentation in colon histology images: The glas challenge contest
K Sirinukunwattana, JPW Pluim, H Chen, X Qi, PA Heng, YB Guo, ...
Medical image analysis 35, 489-502, 2017
Mitosis detection in breast cancer histological images An ICPR 2012 contest
L Roux, D Racoceanu, N Loménie, M Kulikova, H Irshad, J Klossa, ...
Journal of pathology informatics 4, 2013
Recurrent radial basis function network for time-series prediction
R Zemouri, D Racoceanu, N Zerhouni
Engineering Applications of Artificial Intelligence 16 (5-6), 453-463, 2003
Efficient deep learning model for mitosis detection using breast histopathology images
M Saha, C Chakraborty, D Racoceanu
Computerized Medical Imaging and Graphics 64, 29-40, 2018
Automatic breast cancer grading of histopathological images
JR Dalle, WK Leow, D Racoceanu, AE Tutac, TC Putti
2008 30th Annual International Conference of the IEEE Engineering in …, 2008
Time-efficient sparse analysis of histopathological whole slide images
CH Huang, A Veillard, L Roux, N Loménie, D Racoceanu
Computerized medical imaging and graphics 35 (7-8), 579-591, 2011
Contribution à la surveillance des systèmes de production à l'aide des réseaux de neurones dynamiques: Application à la e-maintenance
R Zemouri
Université de Franche-Comté, 2003
Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach
H Irshad, S Jalali, L Roux, D Racoceanu, LJ Hwee, G Le Naour, F Capron
Journal of pathology informatics 4 (Suppl), 2013
Nuclear pleomorphism scoring by selective cell nuclei detection.
JR Dalle, H Li, CH Huang, WK Leow, D Racoceanu, TC Putti
WACV, 2009
Deep learning in the biomedical applications: Recent and future status
R Zemouri, N Zerhouni, D Racoceanu
Applied Sciences 9 (8), 1526, 2019
Knowledge-guided semantic indexing of breast cancer histopathology images
AE Tutac, D Racoceanu, T Putti, W Xiong, WK Leow, V Cretu
2008 international conference on biomedical engineering and informatics 2 …, 2008
New trends to support independence in persons with mild dementia–a mini-review
M Mokhtari, H Aloulou, T Tiberghien, J Biswas, D Racoceanu, P Yap
Gerontology 58 (6), 554-563, 2012
Point set morphological filtering and semantic spatial configuration modeling: Application to microscopic image and bio-structure analysis
N Loménie, D Racoceanu
Pattern Recognition 45 (8), 2894-2911, 2012
Contribution à la surveillance des Systèmes de Production en utilisant les Techniques de l’Intelligence Artificielle
D Racoceanu
Habilitation à diriger des recherches, Université de FRANCHE COMTÉ de …, 2006
Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography
A Depeursinge, D Racoceanu, J Iavindrasana, G Cohen, A Platon, ...
Artificial intelligence in medicine 50 (1), 13-21, 2010
A neuro-fuzzy monitoring system: Application to flexible production systems
N Palluat, D Racoceanu, N Zerhouni
Computers in Industry 57 (6), 528-538, 2006
Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology
H Irshad, A Gouaillard, L Roux, D Racoceanu
Computerized Medical Imaging and Graphics 38 (5), 390-402, 2014
IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006.
C Lacoste, JP Chevallet, JH Lim, X Wei, D Racoceanu, DTH Le, ...
CLEF (Working Notes), 2006
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