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Daniel Racoceanu
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- affiliation: Sorbonne University, Paris, France
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2020 – today
- 2024
- [j17]Xiang Liu
, Wanming Hu
Multi-scale feature fusion for prediction of IDH1 mutations in glioma histopathological images. Comput. Methods Programs Biomed. 248: 108116 (2024) - [i11]Leopold Hebert-Stevens, Gabriel Jimenez, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
Graph Theory and GNNs to Unravel the Topographical Organization of Brain Lesions in Variants of Alzheimer's Disease Progression. CoRR abs/2403.00636 (2024) - [i10]Mehdi Ounissi, Ilias Sarbout, Jean-Pierre Hugot, Christine Martinez-Vinson, Dominique Berrebi, Daniel Racoceanu:
Scalable, Trustworthy Generative Model for Virtual Multi-Staining from H&E Whole Slide Images. CoRR abs/2407.00098 (2024) - 2023
- [c49]J. Arslan, Mehdi Ounissi, H. Luo, M. Lacroix, P. Dupré, P. Kumar, Arran Hodgkinson, S. Dandou, Romain M. Larive, C. Pignodel, L. Le Cam, Ovidiu Radulescu, Daniel Racoceanu:
Efficient 3D reconstruction of whole slide images in melanoma. Digital and Computational Pathology 2023 - [c48]Gabriel Jimenez, Pablo Mas, Anuradha Kar, Julien Peyrache, Léa Ingrassia, Susana Boluda, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
A meta-graph approach for analyzing whole slide histopathological images of human brain tissue with Alzheimer's disease biomarkers. Digital and Computational Pathology 2023 - [i9]Gabriel Jimenez, Daniel Racoceanu:
Computational Pathology for Brain Disorders. CoRR abs/2301.07030 (2023) - [i8]Gabriel Jimenez, Anuradha Kar, Mehdi Ounissi, Léa Ingrassia, Susana Boluda, Benoît Delatour, Lev Stimmer, Daniel Racoceanu:
Visual deep learning-based explanation for neuritic plaques segmentation in Alzheimer's Disease using weakly annotated whole slide histopathological images. CoRR abs/2302.08511 (2023) - [i7]Guanghui Fu, Gabriel Jimenez, Sophie Loizillon, Lydia Chougar, Didier Dormont, Romain Valabrègue, Ninon Burgos, Stéphane Lehéricy, Daniel Racoceanu, Olivier Colliot:
Frequency Disentangled Learning for Segmentation of Midbrain Structures from Quantitative Susceptibility Mapping Data. CoRR abs/2302.12980 (2023) - [i6]Mehdi Ounissi, Morwena Latouche, Daniel Racoceanu:
Phagocytosis Unveiled: A Scalable and Interpretable Deep learning Framework for Neurodegenerative Disease Analysis. CoRR abs/2304.13764 (2023) - 2022
- [c47]Gabriel Jimenez
Visual Deep Learning-Based Explanation for Neuritic Plaques Segmentation in Alzheimer's Disease Using Weakly Annotated Whole Slide Histopathological Images. MICCAI (2) 2022: 336-344 - [c46]Kristyna Manousková, Valentin Abadie, Mehdi Ounissi, Gabriel Jimenez, Lev Stimmer, Benoît Delatour, Stanley Durrleman, Daniel Racoceanu:
Tau protein discrete aggregates in Alzheimer's disease: neuritic plaques and tangles detection and segmentation using computational histopathology. Digital and Computational Pathology 2022 - [i5]Guanghui Fu, Gabriel Jimenez, Sophie Loizillon, Rosana El Jurdi, Lydia Chougar, Didier Dormont, Romain Valabrègue, Ninon Burgos, Stéphane Lehéricy, Daniel Racoceanu, Olivier Colliot
Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI. CoRR abs/2211.01353 (2022) - 2021
- [c45]Fedra Trujillano
Corn Crops Identification Using Multispectral Images from Unmanned Aircraft Systems. IGARSS 2021: 4712-4715 - 2020
- [e8]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12261, Springer 2020, ISBN 978-3-030-59709-2 [contents] - [e7]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part II. Lecture Notes in Computer Science 12262, Springer 2020, ISBN 978-3-030-59712-2 [contents] - [e6]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part III. Lecture Notes in Computer Science 12263, Springer 2020, ISBN 978-3-030-59715-3 [contents] - [e5]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part IV. Lecture Notes in Computer Science 12264, Springer 2020, ISBN 978-3-030-59718-4 [contents] - [e4]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part V. Lecture Notes in Computer Science 12265, Springer 2020, ISBN 978-3-030-59721-4 [contents] - [e3]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VI. Lecture Notes in Computer Science 12266, Springer 2020, ISBN 978-3-030-59724-5 [contents] - [e2]Anne L. Martel
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part VII. Lecture Notes in Computer Science 12267, Springer 2020, ISBN 978-3-030-59727-6 [contents]
2010 – 2019
- 2019
- [e1]Natasha Leporé, Jorge Brieva, Eduardo Romero, Daniel Racoceanu, Leo Joskowicz:
Processing and Analysis of Biomedical Information - First International SIPAIM Workshop, SaMBa 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Revised Selected Papers. Lecture Notes in Computer Science 11379, Springer 2019, ISBN 978-3-030-13834-9 [contents] - 2018
- [j16]Monjoy Saha
Efficient deep learning model for mitosis detection using breast histopathology images. Comput. Medical Imaging Graph. 64: 29-40 (2018) - [i4]Chao-Hui Huang, Daniel Racoceanu:
eXclusive Autoencoder (XAE) for Nucleus Detection and Classification on Hematoxylin and Eosin (H&E) Stained Histopathological Images. CoRR abs/1811.11243 (2018) - 2017
- [j15]Daniel Racoceanu
Preface. Comput. Medical Imaging Graph. 61: 1 (2017) - [j14]Korsuk Sirinukunwattana
Gland segmentation in colon histology images: The glas challenge contest. Medical Image Anal. 35: 489-502 (2017) - [c44]Bassem Ben Cheikh, Nicolas Elie
Spatial interaction analysis with graph based mathematical morphology for histopathology. ISBI 2017: 813-817 - [c43]Bassem Ben Cheikh, Catherine Bor-Angelier, Daniel Racoceanu
A model of tumor architecture and spatial interactions with tumor microenvironment in breast carcinoma. Digital Pathology 2017: 101400C - [c42]Chao-Hui Huang, Daniel Racoceanu
Automated high-grade prostate cancer detection and ranking on whole slide images. Digital Pathology 2017: 101400A - [c41]Yannick L. Kergosien, Daniel Racoceanu
Semantic knowledge for histopathological image analysis: from ontologies to processing portals and deep learning. SIPAIM 2017: 105721F - [c40]Oumeima Laifa, Delphine Le Guillou-Buffello, Daniel Racoceanu
Tumor angiogenesis assessment using multi-fluorescent scans on murine slices by Markov random field framework. SIPAIM 2017: 1057208 - [c39]Laura Marin, Daniel Racoceanu
Prostate cancer: computer-aided diagnosis on multiparametric MRI. SIPAIM 2017: 1057213 - 2016
- [j13]Sreetama Basu, Wei Tsang Ooi
Neurite Tracing With Object Process. IEEE Trans. Medical Imaging 35(6): 1443-1451 (2016) - [c38]Daniel Salas, Jens Gustedt, Daniel Racoceanu, Isabelle Perseil:
Resource-Centered Distributed Processing of Large Histopathology Images. CSE/EUC/DCABES 2016: 367-370 - [c37]Bassem Ben Cheikh, Philippe Bertheau, Daniel Racoceanu
A structure-based approach for colon gland segmentation in digital pathology. Digital Pathology 2016: 97910J - [i3]Korsuk Sirinukunwattana, Josien P. W. Pluim, Hao Chen, Xiaojuan Qi, Pheng-Ann Heng, Yun Bo Guo, Li Yang Wang, Bogdan J. Matuszewski, Elia Bruni, Urko Sanchez, Anton Böhm, Olaf Ronneberger, Bassem Ben Cheikh, Daniel Racoceanu, Philipp Kainz, Michael Pfeiffer, Martin Urschler, David R. J. Snead, Nasir M. Rajpoot:
Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest. CoRR abs/1603.00275 (2016) - 2015
- [j12]Daniel Racoceanu
Breakthrough Technologies in Digital Pathology. Comput. Medical Imaging Graph. 42: 1 (2015) - [j11]Daniel Racoceanu
Towards semantic-driven high-content image analysis: An operational instantiation for mitosis detection in digital histopathology. Comput. Medical Imaging Graph. 42: 2-15 (2015) - 2014
- [j10]Humayun Irshad
Multispectral band selection and spatial characterization: Application to mitosis detection in breast cancer histopathology. Comput. Medical Imaging Graph. 38(5): 390-402 (2014) - [j9]Antoine Fagette, Nicolas Courty, Daniel Racoceanu
Unsupervised dense crowd detection by multiscale texture analysis. Pattern Recognit. Lett. 44: 126-133 (2014) - [c36]Sreetama Basu, Daniel Racoceanu
Reconstructing neuronal morphology from microscopy stacks using fast marching. ICIP 2014: 3597-3601 - [c35]Patrick Jamet, Stephen Chai Kheh Chew, Antoine Fagette, Jean-Yves Dufour, Daniel Racoceanu
Statistically Representative Cloud of Particles for Crowd Flow Tracking. ICPRAM (Selected Papers) 2014: 237-251 - [c34]Antoine Fagette, Patrick Jamet, Daniel Racoceanu, Jean-Yves Dufour:
Particle Video for Crowd Flow Tracking - Entry-Exit Area and Dynamic Occlusion Detection. ICPRAM 2014: 445-452 - [c33]Humayun Irshad, Alexandre Gouaillard, Ludovic Roux, Daniel Racoceanu
Spectral band selection for mitosis detection in histopathology. ISBI 2014: 1279-1282 - [c32]Sreetama Basu, Wei Tsang Ooi
Improved marked point process priors for single neurite tracing. PRNI 2014: 1-4 - 2013
- [c31]Stephane Ulysse Rigaud, Chao-Hui Huang, Sohail Ahmed, Joo-Hwee Lim, Daniel Racoceanu
An analysis-synthesis approach for neurosphere modelisation under phase-contrast microscopy. EMBC 2013: 3989-3992 - [c30]Humayun Irshad
Multi-channels statistical and morphological features based mitosis detection in breast cancer histopathology. EMBC 2013: 6091-6094 - [c29]Sreetama Basu, Maria S. Kulikova, Elena A. Zhizhina, Wei Tsang Ooi
A Stochastic Model for Automatic Extraction of 3D Neuronal Morphology. MICCAI (1) 2013: 396-403 - [i2]Humayun Irshad, Alexandre Gouaillard, Ludovic Roux, Daniel Racoceanu:
Multispectral Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology. CoRR abs/1304.4041 (2013) - 2012
- [j8]Nicolas Loménie
Point set morphological filtering and semantic spatial configuration modeling: Application to microscopic image and bio-structure analysis. Pattern Recognit. 45(8): 2894-2911 (2012) - [j7]Chao-Hui Huang, Shvetha Sankaran, Daniel Racoceanu
Online 3-D Tracking of Suspension Living Cells Imaged with Phase-Contrast Microscopy. IEEE Trans. Biomed. Eng. 59(7): 1924-1933 (2012) - [c28]Antoine Veillard, Stéphane Bressan, Daniel Racoceanu
SVM-based Framework for the Robust Extraction of Objects from Histopathological Images Using Color, Texture, Scale and Geometry. ICMLA (1) 2012: 70-75 - [c27]Antoine Veillard, Daniel Racoceanu
pRBF Kernels: A Framework for the Incorporation of Task-Specific Properties into Support Vector Methods. ICMLA (1) 2012: 156-161 - [c26]Stephane Ulysse Rigaud, Nicolas Loménie
Neurosphere fate prediction: An analysis-synthesis approach for feature extraction. IJCNN 2012: 1-7 - [c25]Maria S. Kulikova, Antoine Veillard, Ludovic Roux, Daniel Racoceanu
Nuclei extraction from histopathological images using a marked point process approach. Image Processing 2012: 831428 - 2011
- [j6]Chao-Hui Huang, Antoine Veillard, Ludovic Roux, Nicolas Loménie
Time-efficient sparse analysis of histopathological whole slide images. Comput. Medical Imaging Graph. 35(7-8): 579-591 (2011) - [c24]Antoine Veillard, Daniel Racoceanu
Incorporating Prior-Knowledge in Support Vector Machines by Kernel Adaptation. ICTAI 2011: 591-596 - [c23]Pierre Cagnac, Noel Di Noia, Chao-Hui Huang, Daniel Racoceanu
Consciousness-driven model for visual attention. IJCNN 2011: 1061-1066 - 2010
- [j5]Adrien Depeursinge
Fusing visual and clinical information for lung tissue classification in high-resolution computed tomography. Artif. Intell. Medicine 50(1): 13-21 (2010) - [j4]Wei Xiong, Sim Heng Ong, Joo-Hwee Lim, Kelvin W. C. Foong
Automatic Area Classification in Peripheral Blood Smears. IEEE Trans. Biomed. Eng. 57(8): 1982-1990 (2010) - [c22]Antoine Veillard, Nicolas Loménie
An Exploration Scheme for Large Images: Application to Breast Cancer Grading. ICPR 2010: 3472-3475 - [c21]Antoine Veillard, Elvina Melissa, Cassandra Theodora, Daniel Racoceanu
Support Vector Methods for Sentence Level Machine Translation Evaluation. ICTAI (2) 2010: 347-348 - [c20]Chao-Hui Huang, Daniel Racoceanu
Bio-inspired computer visual system using GPU and Visual Pattern Assessment Language (ViPAL): Application on breast cancer prognosis. IJCNN 2010: 1-8 - [c19]Roxana Oana Teodorescu, Daniel Racoceanu
Parkinson's disease prediction using diffusion-based atlas approach. Computer-Aided Diagnosis 2010: 762426
2000 – 2009
- 2009
- [c18]Wei Xiong, S. H. Ong, Christina Kang, Joo-Hwee Lim, Jiang Liu
Cell Clumping Quantification and Automatic Area Classification in Peripheral Blood Smear Images. BMEI 2009: 1-5 - [c17]Razvan-Dorel Cioarga, Mihai V. Micea
Emergent Behavior Control Patterns in Robotic Collectives. ICIRA 2009: 165-173 - [c16]Chao-Hui Huang, Wee Kheng Leow, Daniel Racoceanu
A Cellular Neural Network as a Principal Component Analyzer. IJCNN 2009: 1163-1170 - [c15]Adina Eunice Tutac, Daniel Racoceanu
Toward translational incremental similarity-based reasoning in breast cancer grading. Computer-Aided Diagnosis 2009: 72603C - [c14]Jean-Romain Dalle, Hao Li, Chao-Hui Huang, Wee Kheng Leow, Daniel Racoceanu, Thomas C. Putti:
Nuclear pleomorphism scoring by selective cell nuclei detection. WACV 2009 - 2008
- [c13]Adina Eunice Tutac, Daniel Racoceanu
Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images. BMEI (2) 2008: 107-112 - [c12]Wei Xiong, Sim Heng Ong, Joo-Hwee Lim, Nn Tung, Jiang Liu
Automatic working area classification in peripheral blood smears using spatial distribution features across scales. ICPR 2008: 1-4 - [i1]Roxana Teodorescu, Daniel Racoceanu, Wee Kheng Leow, Vladimir Cretu:
Prospective Study for Semantic Inter-Media Fusion in Content-Based Medical Image Retrieval. CoRR abs/0811.4717 (2008) - 2007
- [c11]Bo Qiu, Daniel Racoceanu
Finding Image Structure by Hierarchal Segmentation. ICME 2007: 1419-1422 - 2006
- [j3]N. Palluat, Daniel Racoceanu
A neuro-fuzzy monitoring system: Application to flexible production systems. Comput. Ind. 57(6): 528-538 (2006) - [c10]Daniel Racoceanu
A Semantic Fusion Approach Between Medical Images and Reports Using UMLS. AIRS 2006: 460-475 - [c9]Bo Qiu, Daniel Racoceanu
Stripe: Image Feature Based on a New Grid Method and Its Application in ImageCLEF. AIRS 2006: 489-496 - [c8]Caroline Lacoste, Jean-Pierre Chevallet, Joo-Hwee Lim, Diem Thi Hoang Le, Wei Xiong, Daniel Racoceanu
Inter-media Concept-Based Medical Image Indexing and Retrieval with UMLS at IPAL. CLEF 2006: 694-701 - [c7]Caroline Lacoste, Jean-Pierre Chevallet, Joo-Hwee Lim, Xiong Wei, Daniel Racoceanu, Diem Thi Hoang Le, Roxana Teodorescu, Nicolas Vuillemenot:
IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006. CLEF (Working Notes) 2006 - 2005
- [j2]N. Palluat, Daniel Racoceanu
Utilisation des réseaux de neurones temporels pour le pronostic et la surveillance dynamique. Etude comparative de trois réseaux de neurones récurrents. Rev. d'Intelligence Artif. 19(6): 913-950 (2005) - 2004
- [c6]Maxime Monnin, Daniel Racoceanu
Overview on diagnosis methods using artificial intelligence application of fuzzy Petri nets. RAM 2004: 740-745 - 2003
- [c5]Daniel Racoceanu
Fuzzy Petri nets for monitoring and recovery. ICRA 2003: 4318-4323 - 2002
- [j1]Ryad A. Zemouri
Réseaux de neurones récurrents à fonctions de base radiales: RRFR Application au pronostic. Rev. d'Intelligence Artif. 16(3): 307-338 (2002) - [c4]Daniel Racoceanu
Modular Modeling and Analysis of a Distributed Production System with Distant Specialised Maintenance. ICRA 2002: 4046-4052 - 2001
- [c3]Ryad A. Zemouri, Daniel Racoceanu, Noureddine Zerhouni:
The RRBF. Dynamic representation of time in radial basis function network. ETFA (2) 2001: 737-740 - [c2]Ryad A. Zemouri
A Petri net Graphic Method of Reduction Using Birth-death Processes. ICRA 2001: 46-51
1990 – 1999
- 1994
- [c1]Daniel Racoceanu, Abdellah El Moudni, Michel Ferney, S. Zerhouni:
Use of an homographic transformation jointly to the singular perturbation for the resolution of Markov chains: application to the operation safety study. ICRA 1994: 3544-3549
Coauthor Index
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