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Daniel Racoceanu

Professor @ Sorbonne University, Faculty of Science and Engineering, Paris, France PI @ Paris Brain Institute (ICM), Inria team Aramis, Faculty of Medicine, Sorbonne University
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Current affiliations
  • 542032
  • 542029
  • 413221
Researcher identifiers


**Biography** Professor in BioMedical Image, Pattern Recognition, Machine / Deep Learning and Information / Data Analytics at Sorbonne University, and Principal Investigator at the Paris Brain Institute[\[1\]](#_ftn1) within the INRIA team “Aramis Lab”, my research is focusing on microscopic biomedical image analysis, pattern recognition (including machine & deep learning) and computational integrative pathology, by exploring novel explainable artificial intelligence mechanisms. Dr.Habil./HDR (2006) and Ph.D. (1997) of the Univ. of Franche-Comté, Besançon, France, I was Project Manager at General Electric, before joining, in 1999, a chair of Associate Professor at University of Besançon & Research Fellow at FEMTO-ST Institute - UMR CNRS 6174. From 2005 to 2014, I participated to the creation and the development of the International Joint Research Unit/Lab IPAL (UMI CNRS 2955) Singapore, being the Director (from 2008 to 2014) of this joint research venture created between Sorbonne University, the French National Center for Scientific Research (CNRS), the National University of Singapore (NUS) and the Agency for Science, Technology and Research (A\*STAR). From 2009 to 2015, I was Professor at the School of Computing, National University of Singapore. From 2014 to 2016, I was a member of the Executive Board of the University Institute of Health Engineering of the Sorbonne University, being also co-Director of the Cancer Theranostics research team at the Bioimaging Lab (LIB - CNRS UMR 7371, Inserm U 1146). From 2016 to 2018 I was Professor in BioMedical Image and Data Analytics at the Pontifical Catholic University of Peru. Member of the European Society for Digital Integrative Pathology (ESDIP) Advisory Board since 2020, I was President (2018-2020) and Vice-President (2016-2018) of this European society. From 2018 to 2022, I was member of MICCAI (Medical Image Computing & Computer Assisted Intervention) Board of Directors. Besides being the MICCAI 2020 general chair, I was also involved in the MICCAI 2021 and MICCAI 2022 organization committees. --- [**\[1\]**](#_ftnref1) Paris Brain Institute (Institut du Cerveau – ICM) - Stakeholders : Sorbonne University and French National Center for Scientific Research (CNRS UMR7225), French National Institute of Health and Medical Research - Inserm U1127 and AP-HP (Greater Paris University Hospitals) - UM75.


Computational Pathology Explainable Artificial Intelligence Medical image analysis Biomedical image analysis Deep Learning Machine Learning Computer Vision


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Deep Learning Using Images of the Retina for Assessment of Severity of Neurological Dysfunction in Parkinson Disease

Janan Arslan , Daniel Racoceanu , Kurt K Benke
JAMA Ophthalmology, 2023, 141 (3), pp.240-241. ⟨10.1001/jamaophthalmol.2022.6036⟩
Journal articles hal-04036382v1
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Explicabilité en Intelligence Artificielle ; vers une IA Responsable

Daniel Racoceanu , Mehdi Ounissi , Yannick L. Kergosien
Techniques de l'Ingénieur, 2022
Journal articles hal-03936135v1

Weakly Supervised Framework for Cancer Region Detection of Hepatocellular Carcinoma in Whole-Slide Pathologic Images Based on Multiscale Attention Convolutional Neural Network

Songhui Diao , Yinli Tian , Wanming Hu , Jiaxin Hou , Ricardo Lambo
American Journal of Pathology, 2022, 192 (3), pp.553-563. ⟨10.1016/j.ajpath.2021.11.009⟩
Journal articles hal-03677649v1
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Best Practice Recommendations for the Implementation of a Digital Pathology Workflow in the Anatomic Pathology Laboratory by the European Society of Digital and Integrative Pathology (ESDIP)

Filippo Fraggetta , Vincenzo L’imperio , David Ameisen , Rita Carvalho , Sabine Leh
Diagnostics, 2021, 11 (11), pp.2167. ⟨10.3390/diagnostics11112167⟩
Journal articles hal-03456592v1
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Deep Learning for Semantic Segmentation vs. Classification in Computational Pathology: Application to Mitosis Analysis in Breast Cancer Grading

Gabriel Jiménez , Daniel Racoceanu
Frontiers in Bioengineering and Biotechnology, 2019, 7, pp.145. ⟨10.3389/fbioe.2019.00145⟩
Journal articles hal-02182488v1
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Deep Learning in the Biomedical Applications: Recent and Future Status

Ryad Zemouri , Noureddine Zerhouni , Daniel Racoceanu
Applied Sciences, 2019, 9 (8), pp.1526. ⟨10.3390/app9081526⟩
Journal articles hal-02170880v1
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Efficient deep learning model for mitosis detection using breast histopathology images

Monjoy Saha , Chandan Chakraborty , Daniel Racoceanu
Computerized Medical Imaging and Graphics, 2018, 64, pp.29-40. ⟨10.1016/j.compmedimag.2017.12.001⟩
Journal articles hal-03140981v1
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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 , Bram van Ginneken , Nico Karssemeijer
JAMA Cardiology, 2017, 318, ⟨10.1001/jama.2017.14585⟩
Journal articles hal-03140979v1
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Semantic Integrative Digital Pathology: Insights on Microsemiological Semantics and Image Analysis Scalability

Daniel Racoceanu , Frédérique Capron
Pathobiology, 2016, 83 (2-3), pp.148-155. ⟨10.1159/000443964⟩
Journal articles hal-01365808v1
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Sustainable Formal Representation Of Breast Cancer Grading Histopathological Knowledge

K. Traore , C. Daniel , M.-C. Jaulent , T. Schrader , Daniel Racoceanu
Diagnostic Pathology, 2016, 9 (1), ⟨10.17629/⟩
Journal articles hal-01366742v1

Towards Efficient Collaborative Digital Pathology: A Pioneer Initiative Of The FlexMIm Project

Jean-Baptiste Yunès , Daniel Racoceanu , David Ameisen , A. Veillard , B. Ben Cheikh
the diagnostic pathology journal, 2016
Journal articles hal-02419474v1
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Neurite Tracing With Object Process

Sreetama Basu , Wei Tsang Ooi , Daniel Racoceanu
IEEE Transactions on Medical Imaging, 2016, 35 (6), pp. 1443-1451. ⟨10.1109/TMI.2016.2515068⟩
Journal articles hal-01366490v1
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Towards semantic-driven high-content image analysis: An operational instantiation for mitosis detection in digital histopathology

Daniel Racoceanu , F Capron
Computerized Medical Imaging and Graphics, 2015, 42, pp.2-15. ⟨10.1016/j.compmedimag.2014.09.004⟩
Journal articles hal-01139965v1
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Unsupervised dense crowd detection by multiscale texture analysis

Fagette Antoine , Nicolas Courty , Daniel Racoceanu , Jean-Yves Dufour
Pattern Recognition Letters, 2013, pp.1-27
Journal articles hal-00904210v1
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Point Sets Morphological Filtering and Semantic Spatial Configurations Modeling: application to microscopic image analysis

Nicolas Loménie , Daniel Racoceanu
Pattern Recognition, 2012, 45 (8), pp.2894-2911. ⟨10.1016/j.patcog.2012.01.021⟩
Journal articles hal-00873430v1

New Trends to Support Independence in Persons with Mild Dementia-A Mini-Review

Mounir Mokhtari , Hamdi Aloulou , Thibaut Tiberghien , Jit Biswas , Daniel Racoceanu
Gerontology, 2012, pp.10.1159/000337827
Journal articles hal-00739829v1
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Fusing Visual and Clinical Information for Lung Tissue Classification in HRCT Data

Adrien Depeursinge , Daniel Racoceanu , Jimison Iavindrasana , Gilles Cohen , Alexandra Platon
Artificial Intelligence in Medicine, 2010, pp.ARTMED1118
Journal articles hal-00493108v1
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Automatic Working Area Classification in Peripheral Blood Smears

Wei Xiong , S.H. Ong , Joo-Hwee Lim , Kelvin Foong Weng Chiong , Jiang Liu
IEEE Transactions on Biomedical Engineering, 2010, 57 (8), pp.1982-1990
Journal articles hal-00553282v1
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Time-efficient sparse analysis of histopathological Whole Slide Images

Chao-Hui Huang , Antoine Veillard , Nicolas Lomenie , Daniel Racoceanu , Ludovic Roux
Computerized Medical Imaging and Graphics, 2010, pp.5
Journal articles hal-00553877v1
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A neuro-fuzzy monitoring system. Application to flexible production systems.

Nicolas Palluat , Daniel Racoceanu , Noureddine Zerhouni
Computers in Industry, 2006, 57 (6), pp.528-538. ⟨10.1016/j.compind.2006.02.013⟩
Journal articles hal-00263918v1

Recurrent radial basis function network for time-series prediction

Ryad Zemouri , Daniel Racoceanu , Noureddine Zerhouni
Engineering Applications of Artificial Intelligence, 2003, 16 (5-6), pp.453-463. ⟨10.1016/S0952-1976(03)00063-0⟩
Journal articles hal-02479206v1

Réseaux de neurones récurrents à fonctions de base radiales. Application à la surveillance dynamique

Ryad Zemouri , Daniel Racoceanu , Nourredine Zerhouni
Journal Européen des Systèmes Automatisés (JESA), 2003, 37 (1), pp.49-81. ⟨10.3166/jesa.37.49-81⟩
Journal articles hal-02479204v1

Réseaux de neurones récurrents à fonctions de base radiales : RRFR Application au pronostic

Ryad Zemouri , Daniel Racoceanu , Nourredine Zerhouni
Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, 2003, 16 (3), pp.307-338. ⟨10.3166/ria.16.307-338⟩
Journal articles hal-02479188v1


Ryad Zemouri , Daniel Racoceanu , Noureddine Zerhouni
IFAC Proceedings Volumes, 2002, 35 (1), pp.295-300. ⟨10.3182/20020721-6-ES-1901.01602⟩
Journal articles hal-02479197v1
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Reconstruction vasculaire 3D et analyse de lames virtuelles H&E dans l'étude du mélanome

Janan Arslan , Haocheng Luo , Pawan Kumar , Matthieu Lacroix , Pierrick Dupré
IABM2023 : Colloque Français d'Intelligence Artificielle en Imagerie Biomédicale, Mar 2023, Paris, France
Conference papers hal-03928851v1
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A meta-graph approach for analyzing whole slide histopathological images of human brain tissue with Alzheimer's disease biomarkers

Gabriel Jiménez , Pablo Mas , Anuradha Kar , Léa Ingrassia , Susana Boluda
SPIE Medical Imaging 2022, SPIE, Feb 2023, San Diego, United States
Conference papers hal-03936684v1
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Efficient 3D Reconstruction of H&E Whole Slide Images in Melanoma

Janan Arslan , Mehdi Ounissi , Haocheng Luo , Matthieu Lacroix , Pierrick Dupré
SPIE Medical Imaging 2023, Feb 2023, San Diego, California, United States
Conference papers hal-03834014v2
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Visual deep learning-based explanation for neuritic plaques segmentation in Alzheimer's Disease using weakly annotated whole slide histopathological images

Gabriel Jiménez , Anuradha Kar , Mehdi Ounissi , Léa Ingrassia , Susana Boluda
MICCAI 2022 - 25th International Conference on Medical Image Computing and Computer Assisted Intervention, Sep 2022, Singapore, Singapore. pp.336-344, ⟨10.1007/978-3-031-16434-7_33⟩
Conference papers hal-03810578v1
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Introducing [MALMO]: Mathematical approaches to modelling metabolic plasticity and heterogeneity in Melanoma

Janan Arslan , Laurent Le Cam , Matthieu Lacroix , Emmanuel Faure , Pierrick Dupré
RITS 2022 - Recherche en Imagerie et Technologie pour la Santé, May 2022, Brest, France
Conference papers hal-03834055v1

3D reconstruction and mathematical modelling of whole slide images to elucidate resistance to the targeted therapy in melanoma

Janan Arslan , Pawan Kumar , Arran Hodgkinson , Haocheng Luo , Pierrick Dupré
International Conference in Systems Biology, Oct 2022, Berlin, Germany
Conference papers hal-03814995v1

Data driven mechanistic modeling of oxygen distribution and hypoxia profile in tumor microenvironment

Pawan Kumar , Janan Arslan , Arran Hodgkinson , Haocheng Luo , Sarah Dandou
COMPSYSCAN2022: A complex systems approach to cancer understanding, Oct 2022, Lyon, France
Conference papers hal-03834400v1
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Tau Protein Discrete Aggregates in Alzheimer's Disease: Neuritic Plaques and Tangles Detection and Segmentation using Computational Histopathology

Kristyna Maňoušková , Valentin Abadie , Mehdi Ounissi , Gabriel Jimenez , Lev Stimmer
SPIE Medical Imaging 2022, Feb 2022, San Diego, United States
Conference papers hal-03522378v2

Corn Crops Identification Using Multispectral Images from Unmanned Aircraft Systems

Fedra Trujillano , Jessenia Gonzalez , Carlos Saito , Andres Flores , Daniel Racoceanu
IGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Jul 2021, Brussels, France. pp.4712-4715, ⟨10.1109/IGARSS47720.2021.9553826⟩
Conference papers hal-03677650v1
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Enhanced Methods for Lymphocyte Detection and Segmentation on H&E Stained Images using eXclusive Autoencoders

Chao-Hui Huang , Daniel Racoceanu
IEEE EMBC'20 - 42nd Engineering in Medicine and Biology Conference, Jul 2020, Montreal / Virtual, Canada
Conference papers hal-03140992v1
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Tumor angiogenesis assessment using multi-fluorescent scans on murine slices by Markov Random Field framework

Oumeima Laifa , Delphine Le Guillou-Buffello , Daniel Racoceanu
SIPAIM, 2017, San Andres Island - Colombia, Colombia
Conference papers hal-01615267v1
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Resource-Centered Distributed Processing of Large Histopathology Images

Daniel Salas , Jens Gustedt , Daniel Racoceanu , Isabelle Perseil
19th IEEE International Conference on Computational Science and Engineering, Aug 2016, Paris, France
Conference papers hal-01325648v1
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Preliminary approach for crypt detection in Inflammatory Bowel Disease

Bassem Ben Cheikh , Philippe Bertheau , Daniel Racoceanu
Journées RITS 2015, Mar 2015, Dourdan, France. pp.138-139
Conference papers inserm-01144091v1

An analysis-synthesis approach for neurosphere modelisation under phase-contrast microscopy

Stéphane Rigaud , Chao-Hui Huang , Sohail Ahmed , Joo-Hwee Lim , Daniel Racoceanu
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Jul 2013, Osaka, France. pp.3989-3992, ⟨10.1109/EMBC.2013.6610419⟩
Conference papers hal-02626861v1

Neurosphere fate prediction: An analysis-synthesis approach for feature extraction

Stéphane Rigaud , Nicolas Loménie , Shvetha Sankaran , Sohail Ahmed , Joo-Hwee Lim
2012 International Joint Conference on Neural Networks (IJCNN 2012 - Brisbane), Jun 2012, Brisbane, Australia. pp.1-7, ⟨10.1109/IJCNN.2012.6252628⟩
Conference papers hal-02626907v1
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Un explorateur visuel cognitif (MIcroscope COgnitif - MICO) pour l'histopathologie. Application au diagnostic et à la graduation du cancer du sein.

Gilles Le Naour , Catherine Genestie , Ludovic Roux , Antoine Veillard , Daniel Racoceanu
RITS 2011, Recherche en Imagerie et Technologies pour la Santé, Apr 2011, Rennes, France. pp.119
Conference papers hal-00663408v1
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Spatial Relationships over Sparse Representations

Nicolas Lomenie , Daniel Racoceanu
Spatial Relationships over Sparse Representations, IVCNZ 2009 - Image and Vision Computing, Nov 2010, Wellington, New Zealand
Conference papers hal-00497811v1

Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction

Ryad Zemouri , Daniel Racoceanu , Noureddine Zerhouni , Eugénia Minca , Florin Gheorghe Filip
Intelligent systems and automation: 2nd Mediterranean Conference on Intelligent Systems and Automation (CISA’09), Mar 2009, Zarzis (Tunisia), France. pp.85-90, ⟨10.1063/1.3106518⟩
Conference papers hal-02479235v1
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Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images

Adina Eunice Tutac , Daniel Racoceanu , Thomas Putti , Wei Xiong , Wee-Kheng Leow
BMEI2008, International Conference on BioMedical Engineering and Informatics, May 2008, Sanya, Hainan, China
Conference papers hal-00342275v1

Grids for Content-Based Medical Image Indexing and Retrieval

Sorina Camarasu-Pop , H. Benoit-Cattin , J. Montagnat , D. Racoceanu
ICT4Health, Oncomedia, 2008, Manila, The, Philippines
Conference papers hal-01950484v1
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A fuzzy approach for discrete event systems recovery.

Eugénia Minca , Daniel Racoceanu , Florin Dragomir , Noureddine Zerhouni
IFAC - International Federation of Automatic Control. 4th IFAC Conference on Management and Control of Production and Logistics, MCPL'2007., Sep 2007, Sibiu, Romania. pp.585-590
Conference papers hal-00189140v1

IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006

Caroline Lacoste , Jean-Pierre Chevallet , Joo-Hwee Lim , Wei Xiong , Daniel Raccoceanu
Working Notes for the CLEF 2006 Workshop, 20-22 September Medical Image Track, 2006, Alicante, Spain
Conference papers hal-00954109v1

From the spherical to an elliptic form of the dynamic RBF neural network influence field

Ryad Zemouri , D. Racoceanu , N. Zerhouni
2002 International Joint Conference on Neural Networks (IJCNN), May 2002, Honolulu, United States. pp.107-112, ⟨10.1109/IJCNN.2002.1005452⟩
Conference papers hal-02479186v1

A Petri nets graphic method of reduction using birth-death processes

Ryad Zemouri , D. Racoceanu , N. Zerhouni
2001 ICRA. IEEE International Conference on Robotics and Automation, May 2001, Seoul, South Korea. pp.46-51, ⟨10.1109/ROBOT.2001.932528⟩
Conference papers hal-02479177v1
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Computational Pathology for Brain Disorders

Gabriel Jimenez , Daniel Racoceanu
O. Colliot (Ed.). Machine Learning for Brain Disorders, 197, Springer; Humana, New York, NY, pp.533-572, 2023, Part of the Neuromethods book series (NM,volume 197), 978-1-0716-3195-9. ⟨10.1007/978-1-0716-3195-9_18⟩
Book sections hal-03936550v1
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Innovative Deep Learning Approach for Biomedical Data Instantiation and Visualization

Ryad Zemouri , Daniel Racoceanu
Mourad Elloumi. Deep Learning for Biomedical Data Analysis. Techniques, Approaches, and Applications, Springer International Publishing, pp.171-196, 2021, 978-3-030-71675-2. ⟨10.1007/978-3-030-71676-9_8⟩
Book sections hal-03524662v1
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Contribution à la Surveillance des Systèmes de Production en Utilisant l'Intelligence Artificielle

Daniel Racoceanu
Automatique / Robotique. Université de Franche-Comté, 2006
Habilitation à diriger des recherches tel-00011708v1