SELECTED Publications: (full list bellow - pdf)

Full list

Journals with reviewing committee

  1. Jimenez, G., Racoceanu, D. (2019). Deep Learning for Semantic Segmentation versus Classification in Computational Pathology: Application to mitosis analysis in Breast Cancer grading, Front. Bioeng. Biotechnol., 21 June 2019. [doi] [pdf]
  2. Zemouri, R., Zerhouni, N., Racoceanu, D. (2019). Deep Learning in the Biomedical Applications: Recent and Future Status, Appl. Sci., 9(8), 1526. [doi] [pdf]
  3. Saha, M., Chakraborty, C., Racoceanu, D. (2018). Efficient Deep Learning Model for Mitosis Detection using Breast Histopathology Images, Computerized Medical Imaging and Graphics, 2018 Mar;64:29-40. Epub 2017 Dec 16. [doi] [URL] [pdf]
  4. Ehteshami Bejnordi, B. et al. (2017). Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer, JAMA, 2017; 318(22): 2199-2210. [doi] [URL] [pdf]
  5. Clatici, V. G., Racoceanu, D., Dalle, C., Voicu, C., Thomas-Aragones, L., Servando E. Marron, S. E., Wollina, U., Fica, S. (2017). Perceived Age and Life Style. The specific Contributions of Seven Factors Involved in Health and Beauty. Maedica - A Journal Of Clinical Medicine, 12(3): 112-122. [pdf]
  6. Traore, L., Kergosien, Y., Racoceanu, D. (2017). Bridging the semantic gap between diagnostic histopathology and image analysis, Stud Health Technol Inform., 235:436-440. [pdf] [Pubmed]
  7. Marin, L., Ezziane, M., Comperat, E., Mozer, P., Cancel-Tassin, G., Coté, J.-F., Racoceanu, D., Boudghene, F., Lucidarme, O., Cussenot, O., Renard Penna, R. (2017). Comparison of semi-automated and manual methods to measure the volume of prostate cancer on magnetic resonance imaging, Diagn Interv Imaging, 98(5): 423-428. [pdf] [Pubmed] [DOI]
  8. Sirinukunwattana, K., Pluim, J., Chen, H., Qi, X., Heng, P-A., Bo, Y., Wang, L.Y., Matuszewski, B., Bruni, E., Sanchez, U., Böhm, A. Ronneberger, O., Ben Cheikh, B., Racoceanu, D., Philipp Kainz, P., Pfeiffer, M., Urschler, M., Snead, D., & Rajpoot, N. (2017). Gland Segmentation in Colon Histology Images: The GlaS Challenge Contest. Medical Image Analysis, 2017 Sep, 3;35:489-502. [pdf] [DOI]
  9. Traore, L., Daniel, C, Jaulent, M-C., Schrader, T, Racoceanu, D., Kergosien, Y. (2016). Sustainable formal representation of breast cancer grading histopathological knowledge, The Diagnostic Pathology Journal, 1(2):109. [pdf] [DOI]
  10. Venâncio, R., Ben Cheikh, B., Coron, A. Saegusa-Beecroft, E., Machi, J., Bridal, L., Racoceanu, D., Mamou, J. (2016). Micrometastasis detection guidance by whole-slide image texture analysis in colorectal lymph nodes, The Journal of Diagnostic Patholology, 8:224. [pdf] [DOI]
  11. Racoceanu, D., Ameisen, D., Veillard, A., Ben Cheikh, B. Attieh, E., Brezillon, P., Yunès, J.-B., Temerson, J.-M., Toubiana, L., Verger, V., Pomerol, J.-F., Klossa, J., Lallemand, F., Constant, P., Capron, F., Guettier, C., Phan, N., Bertheau P. (2016). Towards efficient collaborative digital pathology: a pioneer initiative of the FlexMIm project, The Diagnostic Pathology Journal. 2016;8:199. [pdf] [DOI]
  12. Ben Cheikh, B., Bor-Angelier, C., Racoceanu, D. (2016). Graph-Based approach for spatial heterogenity analysis in tumour microenvironement, The Diagnostic Pathology Journal, 8:228. [pdf] [DOI]
  13. Basu, S., Ooi, W.T., & Racoceanu, D. (2016). Neurite tracing with object process, IEEE Transactions on Medical Imaging, 35:6, pp. 1443-1451. [pdf]
  14. Racoceanu D, & Capron F, (2016). Semantic Integrative Digital Pathology. Insights on micro-semiological semantics and image analysis scalability, Pathobiology, 83: 148-155. [pdf]
  15. Racoceanu D, & Capron F, (2015). Towards Semantic-Driven High-Content Image Analysis. An Operational Instantiation for Mitosis Detection in Digital Histopathology, Computerized Medical Imaging and Graphics, Elsevier, 2: 2-15. [pdf] [DOI]
  16. Jamet, P., Chew, S. C. K., Fagette, A., Dufour, J. - Y., & Racoceanu, D. (2015). Statistically Representative Cloud of Particles for Crowd Flow Tracking, In A. Fred, M. De Marsico, & A. Tabbone (Eds.), Pattern Recognition Applications and Methods, 9443: 237–251. [DOI]
  17. Irshad, H., Guaillard, A., Roux, L., & Racoceanu, D. (2014). Multispectral Band Selection and Spatial Characterization: Application to Mitosis Detection in Breast Cancer Histopathology, Computerized Medical Imaging and Graphics, 38(5): 390-402. [pdf] [DOI]
  18. Irshad, H., Veillard, A., Roux, L., & Racoceanu, D. (2014). Methods for Nuclei Detection, Segmentation and Classification in Digital Histopathology: A Review. Current Status and Future Potential, IEEE Reviews on Biomedical Engineering, 7:97-114, manuscript ID: RBME-00024-2013, ISSN: 1937-3333. [pdf] [DOI]
  19. Fagette, A., Courty, N., Racoceanu, D., Dufour, J. Y. (2014). Unsupervised Dense Crowd Detection by Multiscale Texture Analysis, Pattern Recongition Letters, vol. 44, pp. 126–133. [pdf] [DOI]
  20. Roux, L., Racoceanu, D., Loménie, N., Kulikova, M., Irshad, H., Klossa, J., Capron, F., Genestie, C., Le Naour, G., Gurcan, G. (2013). Mitosis detection in breast cancer histological images: ICPR 2012 contest, Journal of Pathology Informatics, 4(1): 2-8. ISSN : 2153-3539. [pdf]
  21. Irshad, H., Jalali, S., Roux, L., Racoceanu, D., Lim, J. H., Le Naour, G., Capron, F. (2013). Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach, Journal of Pathology Informatics, 4(12). [pdf] [DOI]
  22. Huang, C. H., Sankaran, S., Racoceanu, D., Hariharan, S., Ahmed, S. (2012). On-line 3-D Tracking suspension living cells imaged with phase-contrast microscopy, IEEE Trans. Biomed Engineering, 59(7): 1924-1933. [pdf] [DOI]
  23. Mokhtari, M., Aloulou, H., Tiberghien, T., Biswas, J., Racoceanu, D., Yap, P. (2012). New Trends to Support Independence in Persons with Mild Dementia - A Mini-Review, Gerontology, 58: 554-563. [pdf] [DOI]
  24. Loménie, N., Racoceanu, D. (2012). Point set morphological filtering and semantic spatial configuration modeling: applications to microscopic image and bio-structure analysis, , Pattern Recognition, 45(8): 2894-2911. [pdf] [DOI]
  25. Huang, C. H., Veillard, A., Roux, L., Loménie, N., Racoceanu, D. (2011). Time-efficient sparse analysis of histopathological Whole Slide Images, Whole Slide Image Process, Special Issue, Computerized Medical Imaging and Graphics, 35(7): 579-591. [pdf] [DOI]
  26. Xiong, W., Ong, S. H., Lim, J. H., Foong, K., Liu, J., Racoceanu, D., Chong, A. G. L., Tan, K. S. W. (2010). Automatic Area Classification in Peripheral Blood Smears, IEEE Trans. Biomed Engineering, ISSN: 0018-9294, 57(8): 1982-1990. [pdf]
  27. Depeursinge, A., Racoceanu, D., Iavindrasana, J., Cohen, G., Platon, A., Poletti, P. A., Müller, H. (2010). Fusing visual and clinical information for lung tissue classification in HRCT data, Artificial Intelligence in Medicine, Knowledge Discovery and Computer-Based Decision Support in Biomedicine, ISSN: 0933-3657, 50(1): 13-21. [pdf]
  28. Nakai, T., Bagarinao, E., Tanaka, Y., Matsuo, K., Racoceanu, D. (2008). Ontology for fMRI as a Biomedical Informatics Method, Magn. Reson. Med. Sci., ISSN: 1347-3182, 7(3): 141-155. [pdf]
  29. Teodorescu, R. O., Racoceanu, D., Leow, W. K., Cretu, V. I. (2008). Prospective Study for Semantic Inter-Media Fusion in Content-Based medical Image Retrieval, Medical Imaging Technology, 26(1): 1-11. [pdf]
  30. Brezillon, P., Racoceanu, D. (2007). A Context Model for Content Based Medical Image Retrieval, Medical Imaging Technology, 25(5): 327-332. [pdf]
  31. Su, M. J., Chen, H. S., Yang, C. Y., Chen, S. J., Chen, R., Lee, W. J., Cheng, P. H., Yip, P. K., Liu, H. M., Lai, F. P., Racoceanu, D. (2007). Diagnostic Decision Support by Intelligent Medical Image Retrieval with Electrical Medical Record Enhance Dementia Treatment, Medical Imaging Technology, 25(5): 350-355. [pdf]
  32. Palluat, N., Racoceanu, D., Zerhouni, N. (2006). A neuro-fuzzy monitoring system. Application to flexible production systems , Computers in Industry, 57(6): 528-538. [pdf]
  33. Palluat, N., Racoceanu, D., Zerhouni, N. (2005). Utilisation des réseaux de neurones temporels pour le pronostic et la surveillance dynamique. Etude comparative de trois réseaux de neurones récurrents, Revue des sciences et technologies de l’information - RSTI, série Revue d’intelligence artificielle – RIA, 19(6): 913-950. [pdf]
  34. Zemouri, R., Racoceanu, D., Zerhouni, N. (2003). Recurrent Radial Basis Function network for Time-Series Prediction, Engineering Applications of Artificial Intelligence, The International Journal of Intelligent Real-Time Automation, journal IFAC - the International Federation of Automatic Control, Ed. Elsevier Science, 16(5-6): 453-463. [pdf]
  35. Zemouri, R., Racoceanu, D., Zerhouni, N. (2003). Réseaux de Neurones Récurrents a Fonctions de Base radiales. Application à la Surveillance Dynamique, JESA – Journal Européen des Systèmes Automatisés, Ed. Hermès, 37(1): 49-81. ISBN: 2-7462-0834-2. [pdf]
  36. Zemouri, R., Racoceanu, D., Zerhouni, N., Durand, S. (2003). Utilisation Conjointe des Techniques de Modélisation Analytique et de Simulation pour l’Evaluation des Performances en Optimisation de l’Organisation d’un Service de Maintenance, International Journal of Mechanical Production System Engineering, 7: II-3-II-14. [pdf]
  37. Minca, E., Racoceanu, D., Zerhouni, N. (2002). Monitoring Systems Modeling and Analysis Using Fuzzy Petri Nets, Studies in Informatics and Control Journal, 11. [pdf]
  38. Zemouri, R., Racoceanu, D., Zerhouni, N. (2002). Réseaux de Neurones Récurrents à Fonctions de Base radiales. Application au Pronostic, Revue des sciences et technologies de l’information - RSTI, série Revue d’intelligence artificielle- RIA, Ed. Hermès – Lavoisier, Paris, 16(13): 307-338. ISBN: 2-7462-0568-8. [pdf]
  39. Racoceanu, D., El Moudni, A., Zerhouni, N., Ferney, M. (1995). On a new method of Markov chain reduction, Journal of Mathematical Modelling of Systems, 1(3).
  40. Racoceanu, D., El Moudni, A., Zerhouni, N., Ferney, M. (1994). A singular perturbation approach to modelling and resolution of Markov chains, SAMS – System Analysis Modelling Simulation, 15.

International Conference Invitee

  1. Racoceanu, D. (2019). Vessels detection for angiogenesis quantification deep learning and marked point process, ECDP 2019 - 15th European Congress on Digital Pathology, Warwick, UK, 10-13 April, 2019.
  2. Racoceanu, D. (2018). Integrative Computational Histopathology with Latin America. Invited speaker, Computational Pathology Symposium, ECP 2018 - 30th European Congress of Pathology, Bilbao, Spain, 8 to 12 Sept. 2018.
  3. Racoceanu, D. (2018). A Simulation Model for Computational Histopathology issued from the study of Tumour Microenvironment. An instantiation in Breast Carcinomas, Invited speaker, European Congress on Digital Pathology, Helsinki, Finland, May 29th – June 1st, 2018.
  4. Racoceanu, D. (2017). Integrative Computational Pathology and beyond …, Keynote speaker, Digital Pathology and Image Analysis, San Antonio, USA, November 15-16, 2017.
  5. Racoceanu, D. (2016). Integrative digital pathology: semantics and scalable imaging methods, DIGITALPath Europe 2016, London, 18-19 May 2016.
  6. Racoceanu, D. (2016). Are we ready to deal with traceability and massive data in Digital Pathology?, Special session on Biomaker Detection and Discovery in Histopathology Images, 2016 IEEE International Symposium on Biomedical Imaging (IEEE ISBI), Prague, Czech Republic, 13-16 April 2016.
  7. Racoceanu, D. (2015). Semantics, micro-semiology and scalability in future Digital Patholgy, Digital Pathology Congress, 21-22 September 2015, Kuala Lumpur, Malaysia.
  8. Racoceanu, D. (2015). Insights about scalability and big data in Digital Pathology. Recent projects and outcomes, Dublin Pathology 2015. 8th Joint Meeting of the British Division of the IAP and ThePathological Society, June 23rd, 2015, Dublin, Ireland.
  9. Racoceanu, D. (2015). Semantic-Driven Image Exploration for WSI. Scalability for big data, Information Technology in Digital Pathology, AIDPATH EU, May 26th, 2015, Madrid, Spain.
  10. Racoceanu, D. (2014). Semantic-Driven Image Exploration for WSI, Digital Pathology Congress, 4-5 December 2014, London, UK
  11. Racoceanu, D. (2013). Symbolic cognitive approaches using prior knowledge and prior shapes for whole slide image understanding. Roadmap and perspectives inspired by a long-run french-singaporean collaboration, 3rd European Conference on Whole Slide Imaging and Analysis, Heidelberg, Germany, 29th - 30th of Nov. 2013 [slides]
  12. Racoceanu, D. (2010). MICO - A COgnitive virtual MIcroscopy platform for histopathological Whole Slide Images Analysis. Application to Breast Cancer Grading, The 9th Korea-Singapore Joint Workshop on Bioinformatics, 23 Feb. 2010, KAIST - Korea Advanced Institute of Science and Technology, Daejeon, South Korea [slides]
  13. Racoceanu, D. (2008). Translational Breast Cancer Grading System by Automatic Analysis of Histopathology Images in a Virtual Microscope Framework, “Romanian Scientific Diaspora” Conference, Exploratory Workshop: Bioinformatics, 17 – 19 Sept. 2008, Bucharest, Romania. [slides]
  14. Racoceanu, D. (2008). Image Based Reasoning using Medical Knowledge to improve Diagnosis Assistance. Showcases: Early Detection of Brain stroke from brain CT, Histopathology Imaging-based Automatic Breast Cancer Grading, First International Symposium on ICT For Health - ICT4Health 2008, Keynote Lecture, Feb. 29 th -1 st Mar. 2008, Ateneo de Manila University, Manila, Philippines. [pdf]
  15. Racoceanu, D. (2002). Réseaux de Neurones Temporels. Application à la Maintenance Préventive et à la Télémaintenance, Conférence Internationale d’Ingénierie Intégrée - C2I 2002, 25-26 Apr. 2002, Timisoara , Romania. [pdf]

International Conferences with Proceedings

  1. Marin, L., Casado, F., Racoceanu, D. (2019), Classification of prostate cancer based on clinical and omic data using neural networks techniques to improve prognostic power, European Urology Supplements 18(1):e1783. [doi] [Science Direct] [pdf]
  2. Huang, C-H., Racoceanu, D. (2018), eXclusive Autoencoder (XAE) for Nucleus Detection and Classification on Hematoxylin and Eosin (H\&E) Stained Histopathological Images, Computer Vision and Pattern Recognition [pdf] [URL]
  3. Marin, L., Casado, F., Racoceanu, D. (2018), An integrative computational pathology approach to classify prostate cancer. Combining phenotypical, genomic and tumor microenvironment figures using deep learning, European Congress on Digital Pathology, Helsinki, Finland, May 29th – June 1st, 2018. [pdf]
  4. Trujillano, F., Flores, A., Saito, C., Balcazar, M., Racoceanu, D. (2018) Corn classification using Deep Learning with UAV imagery. An operational proof of concept, IEEE Colombian Conference on Applications in Computational Intelligence, Medellín, Colombia. [pdf]
  5. Kergosien. L. Y., Racoceanu, D. (2017), Semantic knowledge for histopathologic image analysis: from ontologies to processing portals and deep learning, Invited Paper, Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105721F (17 November 2017). [DOI] [pdf] [slides]
  6. Laifa, O., Le Guillou-Buffello, D., Racoceanu, D., (2017), Tumor angiogenesis assessment using multi-fluorescent scans on murine slices by Markov Random Field framework, Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis; 1057208 (17 November 2017). [DOI] [pdf]
  7. Marin, L., Racoceanu, D., Renard Penna, R., Ezziane, M. (2017), Prostate Cancer: Computer Aided-Diagnosis on Multiparametric MRI, Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 1057213 (17 November 2017). [DOI] [pdf]
  8. Venâncio, R., Ben Cheikh, B., Coron, A., Saegusa-Beecroft, E., Machi, J., Racoceanu, D., Bridal, L., Mamou, J. (2017), Relating Quantitative Ultrasound Parameters to Histologic Texture Parameters in Cancerous Human Lymph Nodes, 2017 IEEE International Ultrasonics Symposium, Washington D.C., USA. [DOI] [pdf]
  9. Ben Cheikh, B., Elie, N., Plancoulaine, B., Bor-Angelier, C., Racoceanu, D. (2017), Spatial interaction analysis with graph based mathematical morphology for histopathology, Int. Symp. on Biomedical Imaging – IEEE ISBI, Melbourne, Australia. [pdf]
  10. Laifa, O., Le Guillou – Buffello, D., Griffon, J., Bridal, L., Racoceanu, D. (2017), Tumour Angiogenesis Assesment using Multi-Fluorescent Scans of Murine Tumor Slices, RITS, France. [pdf]
  11. Huang, C-H., Racoceanu, D. (2017). Automated high-grade prostate cancer detection and ranking on whole slide images, SPIE Medical Imaging, Orlando, Florida, United States. [pdf]
  12. Ben Cheikh, B., Bor-Angelier, C., Racoceanu, D. (2017). A Model of Tumor Architecture and Spatial Interactions with the Microenvironement in Breast Carcinoma, SPIE Medical Imaging, Orlando, Florida, United States. [pdf]
  13. Salas, D., Gustedt, J., Racoceanu, D., Perseil. I. (2016). Resource-Centered Distributed Processing of Large Histopathology Images. 19th IEEE International Conference on Computational Science and Engineering, Paris, France. [pdf]
  14. Ben Cheikh, B., Bor-Angelier, C., Racoceanu, D., (2016). Nuclei classification in Immunohistochemical stainings for tumour microenvironement analysis in Digital Pathology, 2016 IEEE International Symposium on Biomedical Imaging, Prague, Czech Republic. [pdf] [poster]
  15. Racoceanu D., Bertheau, P., Veillard, A., Ameisen, D., Ben Cheikh, B., Phan, N., Capron, F., Guettier, C., Brezillon, P., Yunes, J.B., Pomerol, J.F., Verger, V., Constant, P., Lallemand, F., Girard, B., Toubiana, L., Temerson, J.M. (2016), Bridging the gap towards efficient Collaborative Digital Pathology: a pioneer initiative of the FlexMIm project, Med-e-Tel 2016, The International eHealth Telemedecine and Health ICT Forum, Luxembourg. [pdf]
  16. Ben Cheikh, B., Bertheau, P., Racoceanu, D. (2016). A structure-based approach for colon gland segmentation in digital pathology, SPIE Medical Imaging, San Diego, US. [pdf]
  17. Ben Cheikh, B., Racoceanu, D. Cell spatial positioning analysis for gland segmentation in Digital Pathilogy, GlaS: Gland Segmentation in Colon Histology Images, Int. Conf. on Medical Image Computing and Computer Assisted Intervention - MICCAI, Munich, Germany, 5-9 Oct. 2015. [pdf]
  18. Ben Cheikh, B., Bertheau, P., Racoceanu, D. Preliminary approach for crypt detection in Inflammatory Bowel Disease, RITS, Dourdan, France, March 2015. [pdf]
  19. Racoceanu, D., Towards semantic integrative microscopy for high-content imaging in Digital Pathology, 22nd Int. Molecular Medicine Tri-Conference - Molecular Med TRI-CON 2015, St. Francisco, USA, 15-20 Feb. 2015.
  20. Basu, S., Racoceanu, D. Reconstructing Neural Morphology from Microscopy Stacks Using Fast Marching, IEEE ICIP 2014 - International Conference on Image Processing, 27-30 Oct. 2014, Paris, France. [pdf]
  21. Racoceanu, D., Capron, F. Towards Semantic-Driven High-Content Image Analysis. An Operational Instantiation for Mitosis Detection in Digital Histopathology, European Conference on Digital Pathology – ECDP 2014, 18-21 June 2014, Paris, France.
  22. S. Basu, D. Racoceanu, W.-T. Ooi, Improved Marked Point Process Priors for Single Neurite Tracing, Pattern Recognition in Neuroimaging, PRNI 2014, 4-6 June 2014, Germany. [pdf][ieee]
  23. H. Irshad, A. Gouaillard, L. Roux, D. Racoceanu, Spectral Band Selection for Mitosis Detection in Histopathology, ISBI - International Symposium on Biomedical Imaging, 28 April – 2 May 2014, Beijing, China. [pdf]
  24. A. Fagette, P. Jamet, D. Racoceanu, J.-Y. Dufour, Particle Video for Crowd Flow Tracking. Entry-Exit Area and Dynamic Occlusion Detection, ICPRAM 2014, International Conference on Pattern Recognition Application and Methods, 6-8 March 2014, Angers, France. [pdf]
  25. S. Basu, M. Kulikova, E. Zhizhina, W.-T. Ooi, D. Racoceanu, A Stochastic Model for Automatic Extraction of 3D Neuronal Morphology, MICCAI 2013, Int. Conf. on Medical Image Computing and Computer Assisted Intervention, Oct 2013, Osaka, Japan. [pdf]
  26. H. Irshad, L. Roux, D. Racoceanu, Multi-channels Statistical and Morphological Features based Mitosis Detection in Breast Cancer Histopathology, EMBC 2013, International Conference of the IEEE Engineering in Medicine and Biology Society, 3-7 July 2013, Osaka, Japan. [pdf]
  27. S. U. Rigaud, C.-H. Huang, S. Ahmed, J.-H. Lim, D. Racoceanu, An Analysis-Synthesis Approach for Neurosphere Modelisation Under Phase-Contrast Microscopy, EMBC 2013, Int. Conf. IEEE Engineering in Medicine and Biology Society, 3-7 July 2013, Japan. [pdf]
  28. H. Irshad, L. Roux, O. Morere, D. Racoceanu, G. Le Naour, F. Capron, Détection automatique et calcul du compte de mitoses sur lames H&E, RITS 2013 colloque pour la Recherche en Imagerie et Technologies pour la Santé, 8-11 Apr. 2013, Bordeaux, France. [pdf]
  29. A. Veillard, S. Bressan, D. Racoceanu. SVM-based framework for the robust extraction of objects from histopathological images using color, texture, scale and geometry, ICMLA 2012, Int. Conf. on Machine Learning and Applications, Dec. 12-15, 2012, USA. [pdf]
  30. A. Veillard, D. Racoceanu, S. Bressan. pRBF kernels: a framework for the incorporation of task-specific properties into support vector methods, ICMLA2012 - 11th International Conference on Machine Learning and Applications, Dec. 12-15, 2012, USA. [pdf]
  31. H. Irshad, L. Roux, D. Racoceanu, Multi-channel Statistics features based Mitosis Detection in Histopathology, Int. Workshop on Pattern Recognition for Healthcare Analytics, ICPR 2012, Int. Conference on Pattern Recognition, Nov. 11, 2012, Japan. [pdf] [poster]
  32. H. Irshad, S. Jalali, L. Roux, D. Racoceanu, J.-H. Lim, G. Le Naour, F. Capron, Automated Mitosis Detection Using Texture, SIFT Features and HMAX Biologically Inspired Approach, HIMA Histopathology Image Analysis: Image Computing in Digital Pathology, MICCAI Int. Conf. Med. Image Computing Comp. Assisted Intervention, 1-5 Oct. 2012, Nice. [pdf] [post]
  33. A. Veillard. M. Kulikova, D. Racoceanu, Cell Nuclei Extraction from Breast Cancer Histopathology Images Using Color, Texture, Scale and Shape Information, European Congr. on Telepathology & Int. Congr. on Virtual Microscopy, 6-9 June 2012, Italy. [pdf]
  34. S. U. Rigaud, N. Loménie, S. Sankaran, S. Ahmed, J.-H. Lim, D. Racoceanu, Neurosphere fate prediction: An analysis-synthesis approach for feature extraction, IEEE WCCI 2012, IEEE World Congress On Computational Intelligence, IJCNN 2012- International Joint Conference on Neural Networks, June 10-15, 2012, Brisbane, Australia. [pdf]
  35. M. Kulikova, A. Veillard, L. Roux, D. Racoceanu, Nuclei extraction from histopathological images using a marked point process approach, SPIE Medical Imaging, 4-9 Feb.2012, USA. [pdf] [poster]
  36. C. H. Tay, R. Mukundan, D. Racoceanu, Multifractal Analysis of Histopathological Tissue Images, IVCNZ 2011 - Image and Vision Computing New Zealand, Nov. 29 - Dec. 1, 2011, Auckland, New-Zealand. [pdf]
  37. A. Veillard, D. Racoceanu, S. Bressan, Incorporating Prior-Knowledge in Support Vector Machines by Kernel Adaptation, ICTAI 2011 - IEEE International Conference on Tools with Artificial Intelligence, Nov. 7-9, 2011, Boca Raton, USA. [pdf]
  38. G. Le Naour, C. Genestie, L. Roux, A. Veillard, D. Racoceanu, Frédérique Capron, Un explorateur visuel cognitif (MIcroscope COgnitif-MICO) pour l’histopathologie. Application au diagnostic et à la graduation du cancer du sein, RITS 2011, colloque pour la Recherche en Imagerie et Technologies pour la Santé, 6-8 Apr. 2011, Rennes, France. [pdf] [poster]
  39. P. Cagnac, Noël Di Noia, C.-H. Huang, D. Racoceanu, L. Chaudron, “Consciousness-driven Model for Visual Attention,” IEEE International Conference on Neural Networks - IJCNN 2011, Jul. 31-Aug. 5, 2011, San Jose, USA. [pdf]
  40. D. Racoceanu, N. Loménie, L. Roux, Cognitive virtual microscopy: a cognition-driven visual explorer for histopathology – the MICO ANR TecSan 2010 initiatiive, Institut Pasteur International Network Annual Scientific Meeting, 22–23 Nov. 2010, Hong Kong, BMC Proc. 2011; 5(Suppl 1): P77, Published online 2011 January 11. [PubMed]
  41. A. Veillard, E. Melissa, C. Theodora, D. Racoceanu, S. Bressan, Support Vector Methods for Sentence Level Machine Translation Evaluation, ICTAI - IEEE International Conference on Tools with Artificial Intelligence, Oct. 27-29, 2010, Arras, France. [pdf]
  42. A. Veillard, N. Lomenie, D. Racoceanu, An Exploration Scheme for Large Images: application to Breast Cancer Grading, ICPR'2010 - International Conference on Pattern Recognition, August 23-26, 2010, Istanbul, Turkey. [pdf]
  43. C.-H. Huang, D. Racoceanu, L. Roux, T. Putti, Bio-inspired Computer Visual System using GPU and Visual Pattern Assessment Language (ViPAL): Application on Breast Cancer Prognosis, IJCNN 2010 / WCCI 2010 - International Joint Conference on Neural Networks - 2010 IEEE World Congress on Computational Intelligence, Jul. 18-23, 2010, Spain. [pdf]
  44. N. Loménie, D. Racoceanu, L. Roux, The MICO platform: cognitive virtual microscopy for breast cancer grading, 10th European Congress on Telepathology and 4th International Congress on Virtual Microscopy, 1-3 July 2010, Vilnius, Lithuania..
  45. A. E. Tutac, V. I. Cretu, D. Racoceanu, Spatial Representation and Reasoning in Breast Cancer Grading Ontology, IEEE Int. Joint Conferences on Computational Cybernetics and Technical Informatics, May 27-29, 2010, pp. 89-94, ISBN: 978-1-4244-7431-8, Timisoara, Romania.
  46. R. O. Teodorescu, D. Racoceanu, N. Smit, V. I. Cretu, E. K. Tan, L.-L. Chan, Parkinson's disease prediction using diffusion-based atlas approach, SPIE Medical Imaging, Feb. 13-18, 2010, San Diego, USA. [pdf] [slides]
  47. J.-R. Dalle, H. Li, C.-H. Huang, W.-K. Leow, D. Racoceanu, T. Putti, Nuclear Pleomorphism Scoring by Selective Cell Nuclei Detection, WACV 2009 - IEEE Workshop on Applications of Computer Vision, Dec.7-8, 2009, USA. [pdf]
  48. N. Loménie, D. Racoceanu, Spatial Relationships over Sparse Representations, IVCNZ 2009 - Image and Vision Computing New Zealand, 23-25 Nov. 2009, New-Zealand. [pdf]
  49. N. Loménie, L. Roux, D. Balensi, A. Tutac, D. Racoceanu, MICO: the COgnitive virtual MIcroscope project, COGIS’09-COGnitive syst. with Interactive Sensors, 16-18 Nov. 2009, Paris. [pdf] 
  50. R. O. Teodorescu, D. Racoceanu, L.-L. Chan, K.-O. Lovblad, H. Müller; C.-H. Huang, W.-K. Leow, Parkinson’s disease detection using 3D Brain MRI FA map histograms correlated with tract directions, RSNA 2009 -95th Radiological Society of North America Scientific Conference, November 29 to Dec. 4, 2009, Chicago, USA. [slides]
  51. W. Xiong, S.H. Ong, C. Kang, J.-H. Lim, J. Liu, D. Racoceanu, K. Foong, Cell, Clumping Quantification and Automatic Area Classification in Peripheral Blood Smear Images, BMEI 2009 - 2nd International Conference on BioMedical Engineering and Informatics, Published by IEEE Computer Society, 17-19 Oct. 2009, Tianjin, China. [pdf]
  52. L. Roux, A. E. Tutac, N. Loménie, D. Balensi, D. Racoceanu, W.-K. Leow, A. Veillard, J. Klossa, T. C. Putti, A Cognitive Virtual Microscopic Framework for Knowlege-based Exploration of Large Microscopic Images in Breast Cancer Histopathology, IEEE EMBS'09 - 31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, “Engineering the Future of Biomedecine”, Sept. 2-6, 2009, pp. 3697-3702, Minneapolis, USA. [pdf]  
  53. A. E. Tutac, D. Racoceanu, N. Loménie, W.-K. Leow, L. Roux, V. I. Cretu, T. Putti, Knowledge Modeling for Breast Cancer Grading using OWL-DL formalism, The European Journal of Pathology, Springer-Verlag Berlin Heidelberg, H. Höfler ed, vol. 455, suppl.1: pp. 36, ISSN : 0945-6317 (Print) 1432-2307 (Online), Aug. 2009, 22nd Eur. Congr. of Pathology, 4-9 Sept. 2009, Florence, Italy. [pdf]
  54. L. Roux, Adina Tutac, Antoine Veillard, J.-R. Dalle, D. Racoceanu, N. Loménie, J. Klossa, A Cognitive Approach to Microscopy Analysis Applied to Automatic Breast Cancer Grading, The European Journal of Pathology, Springer-Verlag Berlin Heidelberg, H. Höfler ed, vol. 455, suppl.1, pp. 34-35, ISSN : 0945-6317 (Print) 1432-2307 (Online), Aug. 2009, 22nd Eur. Congress of Pathology, 4-9 Sept. 2009, Florence, Italy.
  55. C.-H. Huang, W.-K. Leow, D. Racoceanu, The Cellular Neural Network as a Principal Component Analyzer, IJCNN 2009 - International Joint Conference on Neural Network, pp. 1163–1170, June 14-19, 2009, Atlanta, USA. [pdf]
  56. A. E. Tutac, D. Racoceanu, W.-K. Leow, H. Müller; T. Putti; V. Cretu, Toward Translational Incremental Similarity-Based Reasoning in Breast Cancer Grading, Proceedings SPIE Medical Imaging 2009: Computer-Aided Diagnosis, vol. 7260, 72603C, pp.1-12, ISBN : 978-0-8194-7511-4, 7-12 Feb. 2009, Orlando, USA. [pdf]  
  57. W. Xiong, S.H. Ong, J.H. Lim, N.N. Tung, J. Liu, D. Racoceanu, K. Tan, A. Chong, K. Foong, Automatic Working Area Classification in Peripheral Blood Smears Using Spatial Distribution Features Across Scales, ICPR 2008 - Int. Conf. Pattern Recognition, Dec. 8-11, 2008, USA. [pdf]
  58. A. E. Tutac, D. Racoceanu, W.-K. Leow, J. R. Dalle, T. Putti, W. Xiong, V. Cretu, Translational Approach for Semi-Automatic Breast Cancer Grading Using a Knowledge-Guided Semantic Indexing of Histopathology Images, 3rd Microscopic Image Analysis with Application in Biology MIAAB Workshop, in conj. with MICCAI 2008, 11th International Conference on Medical Image Computing and Computer Assisted Intervention, 6-10 Sept, 2008, New-York, USA.[pdf]
  59. R. O. Teodorescu, C. Cernazanu-Glavan, V. I. Cretu, D. Racoceanu, The use of the medical ontology for a semantic-based fusion system in biomedical informatics, IEEE Int. Conf. on Intelligent Comp. Comm. and Processing, vol. 1, pp 265-268, Aug. 2008, Cluj-Napoca, Romania.
  60. J.-R. Dalle, W.-K. Leow, D. Racoceanu, A. E. Tutac, T. C. Putti, Automatic Breast Cancer Grading of Histopathological Images, IEEE EMBS 2008 - Int. Conf. of the IEEE Engineering in Medicine and Biology Society, "Personalized Healthcare through Technology", pp.3052-3055, ISBN: 978-1-4244-1814-5, ISSN: 1557-170X, 20-24 Aug. 2008, Vancouver, Canada. [pdf]  
  61. W. Xiong, J.H. Lim, S.H. Ong, N.N. Tung, J. Liu, D. Racoceanu, K. Tan, A. Chong, K. Foong, Automatic Working Area Classification in Peripheral Blood Smears without Cell Central Zone Extraction, IEEE EMBS 2008 - International Conference of the IEEE Engineering in Medicine and Biology Society, "Personalized Healthcare through Technology", IEEE EMBS, pp.4074-4077, ISBN: 978-1-4244-1814-5, ISSN: 1557-170X, 20-24 Aug. 2008, Vancouver, Canada.  [pdf]
  62. R. O. Teodorescu, V. I. Cretu, D. Racoceanu, The use of Medical Ontology in a knowledge-based semantic Fusion system, IEEE Int. Joint Conf. on Computational Cybernetics and Technical Informatics, June 2008, Timisoara, Romania.
  63. A. E. Tutac, D. Racoceanu, T. Putti, W. Xiong, W.-K. Leow, V. Cretu, Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images, Proceedings of 1st Conference on BioMedical Engineering and Informatics BMEI, Biomedical Engineering and Informatics: New Development and the Future, vol.2, pp. 107-112, ISBN: 978-0-7695-3118-2, 27-30 May 2008, China.  [pdf]
  64. R. Teodorescu, D. Racoceanu, Semantic Inter-Media Fusion Design for a Content-Based Medical Image Retrieval System, JAMIIT Proceedings, ONCO_MEDIA special session in the Japanese Society of Medical Imaging Technology, Annual Meeting, 20th of July 2007, Tsukuba, Japan.
  65. P. Brezillon, D. Racoceanu, Context Modelling in Content-Based Medical Image Retrieval, JAMIIT Proceedings, ONCO_MEDIA special session in JAMIIT (Japanese Society of Medical Imaging Technology) Annual Meeting, 20th of July 2007, Tsukuba, Japan.
  66. B. Qiu, D. Racoceanu, Finding Image Structure by Hierarchical Segmentation, ICME 2007, IEEE Int. Conf. on Multimedia & Expo, July 9-10, 2007, pp. 1419-1422, Beijing, China. [pdf]
  67. M. J. Su, H. S. Chen, C. Y. Yang, S. J. Chen, W. J. Lee, P. H. Cheng, P. K. Yip, H. M. Liu, F. P. Lai, and D. Racoceanu, 9th IEEE International Conference on e-Health Networking, Application and Services, 19-22 June 2007, Taiwan.
  68. ONCO-MEDIA consortium (PI: D. Racoceanu, co-PIs: H. Benoit-Cattin, P. Brezillon, H.-S. Chen, T. Jiang, S. Miguet, H. Muller, T. Nakai, J. Montagnat, R. P. Saldana, Collaborators: L.-L. Chan, J.-P. Chevallet, M. K. Leong, W. K. Leow, J.-H. Lim, D. Lingrand, P. Manalastas, B. Morello, B. Qiu, P. Ruch, L. F. G. Sarmenta, S.-C. Wang), The ONCO-MEDIA project challenges, HealthGrid 2007, 24-27 Apr. 2007, Geneva, Switzerland. [pdf]  
  69. D. Racoceanu, C. Lacoste, R. Teodorescu, N. Vuillemenot, A Semantic Fusion Approach Between Medical Images and Reports Using UMLS, Lecture Notes in Computer Science, Springer Berlin/Heidelberg, H.T. Ng et al. (Eds.): Asian Information Retrieval Symposium, 16-18 Oct. 2006, vol. 4182/2006, ISSN 0302-9743, ISBN 978-3-540-45780-0, pp. 460–475, Singapore. [pdf]
  70. B. Qiu , D. Racoceanu, C. S. Xu, Q. Tian, Stripe: Image Feature Based on a New Grid Method and Its Application in ImageCLEF , Lecture Notes in Computer Science, Springer Berlin/Heidelberg, H.T. Ng et al. (Eds.): Asian Information Retrieval Symposium, 16-18 Oct. 2006, vol. 4182/2006, ISSN 0302-9743, ISBN 978-3-540-45780-0, pp. 489-496, Singapore. [pdf]  
  71. N. Palluat, D. Racoceanu, N. Zerhouni, An UML modelling of a neuro-fuzzy monitoring system. Proc. of the 16th World Congress of the International Federation of Automatic Control, IFAC'2005, 3-8 July 2005, Prague, Czech Rep. [pdf]
  72. A. Ghernaut, D. Racoceanu, N. Zerhouni, Approche duale maintenance-qualité pour la surveillance des systèmes mécatroniques, PENTOM 2005 : Performances et Nouvelles Technologies en Maintenance, 18-21 April 2005, Marrakech, Maroc.
  73. M. Monnin, D. Racoceanu, N. Zerhouni, Overview on diagnosis methods using artificial intelligence, IEEE Conf. Robotics, Automation Mechatronics, 1-3 Dec.2004,Singapore. [pdf]
  74. M. Monnin, N. Palluat, D. Racoceanu, N. Zerhouni, Diagnosis Methods Using Artificial Intelligence. Application of Fuzzy Petri Nets and Neuro-Fuzzy systems, IFAC MCPL 2004 – Conf. on Management and Control of Production and Logistics, 3-5 Nov. 2004, pp.49-56, Chile.  [pdf]
  75. PROTEUS ITEA European Project WP2 TEAM (L. Déchamp, A. Dutech, T. Montroig, X. Qian, D. Racoceanu, I. Rasovska, P. Brézillon, F.Charpillet, J-Y. Jaffray, N. Moine, B. Morello, S. Müller, G. Nguengang, N. Palluat, L.Pelissier), On the Use of Artificial Intelligence for Prognosis and Diagnosis in the PROTEUS E-maintenance platform, IEEE Mechatronics & Robotics 2004, Aachen, Germany, E-Maintenance Special Session, Sept. 13-15, 2004. [pdf]  
  76. N. Palluat, D. Racoceanu, N. Zerhouni, Diagnosis Aid System using a Neuro-Fuzzy Approach, Intelligent Maintenance System - IMS 2004, 15-17 July 2004, Arles, France.  
  77. E. Minca, D. Racoceanu, N. Zerhouni, Fuzzy Petri nets for monitoring systems modeling, Proc. of the 2003 IEEE International Conference on Robotics & Automation, ICRA'2003, 14-19 Sept. 200 3, pp. 4318-4323, Taipei, Taiwan. [pdf]
  78. A. Djouak, D. Racoceanu, N. Zerhouni, Etude d'un Multicapteur Intelligent à base de Réseaux de Neurones, Conf. Int. sur l’Automatisation Ind., 9-11 June 2003, Montréal, Canada. [pdf]  
  79. D. Racoceanu, O. A. Djaffar, Réseaux Neuro-Flous pour la Surveillance des Systèmes, Conf. Int. sur l’Automatisation Industrielle, 9-11 June 2003, Montréal, Canada. [pdf]
  80. R. Zemouri, D. Racoceanu, N. Zerhouni, Application of the Dynamic RBF network in a monitoring problem of production systems, IFAC 2002, July 2002, Barcelona, Spain. [pdf]
  81. R. Zemouri, D. Racoceanu, N. Zerhouni, From the spherical to an elliptic form of the dynamic RBF neural network influence field , 2002 IEEE World Congress on Computational Intelligence, Int. Joint Conference on Neural Networks, IEEE-WCCI/IJCNN 2002, 12-17 May 2002, USA. [pdf]
  82. D. Racoceanu, N. Zerhouni, N. Addouche, Modular Modeling and Analysis of a Distributed Production System with Distant Specialised Maintenance, IEEE ICRA 2002, Proc. of the 2002 IEEE Int. Conf. on Robotics and Automation, 11-15 mai 2002, Washington, USA, pp. 4046-4052. [pdf]
  83. R. Zemouri, D. Racoceanu, N. Zerhouni, A Petri nets graphic method of reduction using birth-death processes, Proc. of the 2001 IEEE International Conference on Robotics & Automation, ICRA'2001, pp. 46-51, 21-26 May 2001, Seoul, Korea (Best paper Award finalist). [pdf]
  84. D. Racoceanu, N. Zerhouni, Use of Singular Perturbations for the Reduction of Manufacturing System Models, Proc. of the 2nd IFAC Conference on Management and Control of Production and Logistics, IFAC - MCPL’2000 [pdf], pp. 352-358, 5-8 July 2000, Grenoble, France.
  85. D. Racoceanu, A. El Moudni, M. Ferney, S. Zerhouni, A near optimal control of Markov chains using discrete singular perturbations in the case of first order polynomial control. Terminal problems , IMACS-SAS’95 Conference, Berlin, Germany, 27-29 June 1995.
  86. D. Racoceanu, A. El Moudni, S. Zerhouni, M. Ferney, Use of an homographic transformation jointly to the singular perturbation for the study of Markov chains. Application to the operational safety study, congres IEEE Robotics and Automation, San Diego, USA, 8-13 May 1994.
  87. D. Racoceanu, A. El Moudni, S. Zerhouni, M. Ferney, A Markov chain singular perturbation resolution, congres 1- Mathmod Vienna, Vienne, Austria, 2-4 February 1994.

- Invited Talks

  1. Racoceanu, D. (2019). Tumor Heterogeneity Analysis, Indexing and Simulation in Computational Pathology, Shenzhen Institute of Advanced Technology (SIAT), Shenzhen, China, 17 Oct. 2019.
  2. Racoceanu, D. (2019). Computational Pathology: A Path Ahead, Café de la Neuroinformatique, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France, 19 Sept. 2019.
  3. Racoceanu, D. (2019). Artificial intelligence for biomedical image analysis applications: lessons learned from personal projects, expertise and contributions, Institut du Cerveau et de la Moelle épinière (ICM), Paris, France, 10 May 2019.
  4. Racoceanu, D. (2018). Artificial Intelligence Applied to Very Large Image Analysis in Medicine (Digital Pathology), Invited Speaker, Día Mundial de las Telecomunicaciones, la Sociedad de la Información, y el Internet, Pontifical Catholic University of Peru, 17 May 2018.
  5. Racoceanu, D. (2017). Intergative Digital Pathology and beyond, Invited Talk at the National University of Colombia, Bogota, Colombia, 9th of May 2017.
  6. Racoceanu, D. (2016). Rossi, F., TERRES D’INNOVATION SINGAPOUR, une plate-forme d’innovation et de R&D unique en Asie, Congres C.U.R.I.E., 6-9 June 2016, Deauville, France.
  7. Racoceanu, D. (2014). Big data in microscopy, French National Center for Scientific Research (CNRS) Research Group - Technologies for Healthcare - GdR STIC-Santé, Lyon, France, 23-25 Sept 2014.
  8. Racoceanu, D. (2014). Towards the future of Digital Pathology, Massachusetts General Hospital, 17 sept 2014, Boston, USA.
  9. Racoceanu, D. (2014). Digital Pathology: a semantic driven protocol for WSI exploration, Harvard Medical School, Beth Israel Deaconess Medical Center, Pathology Dept., 15 sept 2014, Boston, USA.
  10. Racoceanu, D. (2014). Major research results in cognitive multi-scale exploration of high content images at IPAL/BMIU, Bioinformatics Institute A*STAR, Singapore, 7th of Feb. 2014.
  11. Racoceanu, D. (2013). Exploration cognitive symbolique des images biomédicales haut contenu. Application à la gradation des cancers en histopathologie et au suivi de cellules souches par recalage dynamique entre l'analyse 2D et la synthèse 3D, LIRMM UMR CNRS - University of Motpellier II, Invited talk, 24 sept 2013, Montpellier, France.
  12. Racoceanu, D. (2013). Cognitive virtual Microscopy for breast cancer grading in histopathology for Whole Slide Image exploration using a symbolic cognitive vision approach, Centre de Recherche des Cordeliers, LIMICS (Laboratory in Medical Informatics and Knowledge Engineering in e-Health), Inserm UMRS 1142, invited talk, 8 Apr. 2013, Paris, France.
  13. Racoceanu, D. (2013). Symbolic visual approaches using prior knowledge and shapes for high content microscopic images exploration. Roadmap and perspectives inspired by a long-run french-singaporean collaboration, INRIA/CNRS-Sophia Antipolis, Ayin (INRIA) and Morpheme (INRIA/CNRS) research groups, invited talk, 18 Feb 2013, Sophia-Antipolis.
  14. Racoceanu, D. (2013). Approches cognitives symboliques et connaissances/formes a priori pour l'imagerie microscopique haut contenu. Perspectives à travers des projets franco-singapouriens, invited talk, LTSI, Inserm UMRS 1099 - University of Rennes 1, MediCIS team, 14 Feb. 2013, Rennes, France
  15. Racoceanu, D. (2013). Approches visuelles sémantiques en histopathologie, invited talk, Unité BioTICLA - Equipe IMAGIN' Biologie et Thérapies Innovantes des Cancers Localement Agressifs EA 4656 de l'Université de Caen Basse-Normandie, IFR 146 ICORE Centre de Lutte Contre le Cancer François Baclesse, 12 Feb 2013, Caen, France
  16. Racoceanu, D. (2012). Imagerie microscopique haut débit / haut contenu et ses perspectives à travers deux applications développées dans des projets franco-singapouriens, invited talk, Research center of the Brain and Spine Institute (CRICM - Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière), 17 Oct 2012, Paris, France
  17. Racoceanu, D. (2011). Exploration d'une lame virtuelle en utilisant une approche in vitro - in silico – in cognito : Application à la gradation du cancer du sein en histopathologie, Functional Imaging Lab. (LIF), French National Institute of Health and Medical Research (INSERM), Faculty of Medecine Pierre and Marie Curie - Pitié-Salpêtrière, Dec 1st, 2011, Paris.
  18. Racoceanu, D. (2010). Presentation of the International French-Singaporean Collaboration IPAL – Image & Pervasive Access Lab – UMI CNRS, French-Singaporean Entrepreneurships R&D Committee Opening Meeting, Invited speaker, Organized by the French Chamber of Commerce in Singapore & French Embassy in Singapore, 14 Jan. 2010, Singapore.
  19. Racoceanu, D. (2009). IPAL researches in ontology driven virtual microscopy for breast cancer grading, European COST Action IC0604 Euro-Telepath, Management Committee and 6/7th Working Groups Meetings, 03-04 Dec. 2009, Lausanne, Switzerland
  20. Racoceanu, D. (2008). Image Based Reasoning Systems using Medical Knowledge for Diagnosis Assistance, Invited Talk, Inst. Molecular Cell Biology (IMCB), 27 Feb. 2008, Singapore.
  21. Racoceanu, D. (2005). Monitoring Approach Using Recurrent Radial Basis Function Neural Networks and Neuro-Fuzzy Systems, Invited Talk , Department of Computer Science, School of Computing, National University of Singapore, 7 December 2005.
  22. Racoceanu, D. (2005). Dynamic Monitoring Systems using recurrent neural Networks and neuro-Fuzzy Systems. Nemosys project; Invited Talk, Artificial Intelligence Department, Tsinghua University, Beijing, China, 17 October 2005.

Books chapters

  1. Loménie, N., Racoceanu, D., Stamon, G. (2011). Point Set Analysis: An Image Analysis Point of View for Rapid Prototyping Technologies, in Rapid Prototyping / Book 1", ISBN 978-953-307-970-7, InTech, July 2011. [pdf] [link]
  2. Teodorescu, R. O., Cretu, V. I., Racoceanu, D. (2011). Medical Image Processing and Analysis for Parkinson's Disease Diagnosis and Prognosis, "Biomedical Engineering, Trends, Researches and Technologies", InTech, ISBN: 978-953-307-475-7, Jan. 2011. [pdf] [3000 downloads]
  3. Su, M.-J., Cheng, P.-H., Chen, S.-J., Yang, C.-Y., Yip, P.-K., Racoceanu, D., Chen, H.-S. (2010). Medical Image Intelligent Access Integrated with Electronic Medical Records System for Brain Degenerative Disease, Data Storage, ISBN: 978-953-307-063-6, InTech, April 2010, pp. 201-211. [pdf]
  4. Lacoste, C., Chevallet, J.-P., Lim, J.-H., Le Thi Hoang, D., Xiong, W., Racoceanu, D., Teodorescu, R., Vuillenemot, N. (2007). Inter-Media Concept-Based Medical Image Indexing and Retrieval with UMLS at IPAL, in Lecture Notes in Computer Science, Evaluation of Multilingual and Multi-modal Information Retrieval, vol. 4730/2007, pp. 694-701. [pdf]

Edition of symposium proceedings and scientific journals special issues

  1. Racoceanu, D., Hufnagl, P. (Eds), (2017) Special Issue: "Scalable and Efficient Imaging Technologies for Digital Pathology", CMIG - Computerized Medical Imaging and Graphics, Elsevier, Volume 61, Pages 1-34. Rapid Prototyping / Book 1", ISBN 978-953-307-970-7, InTech, July 2011. [pdf] [URL]
  2. Racoceanu, D., Belhomme, P. (Eds.), Special issue: Breakthrough technologies in digital pathology, Computerized Medical Imaging and Graphics, Elsevier, Vol. 2, June 2015, pp.1, [URL]
  3. Roux, L, Racoceanu, D. Mitosis detection in breast cancer histological images: ICPR 2012 contest, Journal of Pathology Informatics, special issue, vol. 4, no. 1, 30 May 2013, ISSN : 2153-3539. [URL]
  4. Loménie, N., Racoceanu, D., Gouaillard, A. (Eds.), Advances in Bio-Imaging: From Physics to Signal Understanding Issues, State-of-the-Art and Challenges, Springer Series: Advances in Intelligent and Soft Computing, Vol. 120, 2012, 2012, XXII, 246 p., ISBN 978-3-642-25546-5, January 9, 2012. [URL], [SFBI 2011]
  5. Leow, W.-K., Ding, F., Li, H., Racoceanu, D. (Eds.), SinFra’09 - Singaporean-French IPAL Symposium, Proceedings of the symposium with the selected publications, ISBN: 978-981-4277-55-6(CD) / 981-4277-55-X(CD), 18–20 Feb. 2009, Fusionopolis & Institute for Mathematical Sciences, Singapore. [pdf] [URL]
  6. Nakai, T., Racoceanu, D. (Eds.), Special Issue on ONtology and COntext related MEdical image Distributed Intelligent Access, International Symposium of the 26 th Annual Meeting of Japanese Society for Medical Imaging Technology (JAMIT), 20 Jul. 2007, Tsukuba, Japan, Medical Imaging Technology, vol.25, no.5, Nov. 2007. [pdf]

- International Conferences / Symposiums / Workshops organization

  1. MICCAI 2020, Peru – Latin America, General Chair
  2. ECDP 2018, European Conference of Digital Pathology, Helsinki, Finland, Scientific committee.
  3. First University of Waterloo - Sorbonne University seminar: " Crystalizing Transdisciplinary innovation in Health Engineering ", 9-11 May, 2016.
  4. MITOS & ATYPIA @ ICPR 2014, International Medical Benchmark entitled: Mitosis Detection and Atypia assessment in Breast Cancer Histological Images, in the framework of ICPR 2014, Int. Conf. on Pattern Recognition, 24-28 Aug 2014, Stockholm, Sweden. [Challenge]
  5. ECDP 2014, European Conf. of Digital Pathology, Scientific and Organization Committees, 18-20 June 2014, Paris. [Conf]
  6. IJCNN 2013 Special Session: "Computational Intelligence in Bioimage Informatics" (IJCNN-CIBII2013), Int. Joint Conf. on Neural Newtorks IJCNN 2013, Dallas, USA, Aug. 4-9, 2013.
  7. MITOS International Medical Benchmark: Mitosis Detection in Breast Cancer Histological Images, initiative of IPAL in collaboration with the Hôpital de la Pitié-Salpêtrière in the framework of the conference ICPR 2012 - Int. Conf. Pattern Recognition, 11-15 Nov., 2012, Tsukuba, Japan.
  8. Sp. Session : "Consciousness-driven vision: toward a breakthrough in bio-inspired computer vision", 31 July – 5 Aug 2011, IJCNN 2011 - Int. Joint Conf. Neural Networks, USA.
  9. SFBI 2011 – Singaporean - French BioImaging Seminar 2011, 24-25 February. 2011, Biopolis, Singapore. [SFBI2011] (Keynote – Mathias Fink, ESPC, France)
  10. ICT’2010, EU-ASEAN Cooperation opportunities, Networking Session jointly organized by IPAL and SEACOOP, Bruxelles, Belgium, 27-29 September 2010.
  11. Image Understanding - an important step toward Visual Cognition, WCCI 2010 - 2010 IEEE World Congress on Computional Intelligence, Special Session, Chairs: Daniel Racoceanu and Chao-Hui Huang, 18-23 July, 2010, Barcelona, Spain.
  12. SinFra’2009 - Singaporean-French IPAL Symposium, 18–20 February 2009, Fusionopolis, Singapore - Tutorials and Scientific Sessions, D. Racoceanu, J.H Lim, W.K. Leow, General Chairs. [SinFra09] (Keynote - Joseph Sifakis, 2007 ACM Turing award winner)
  13. “Ontology and Context Related Medical Image Distributed Intelligent Access” - ONCO-MEDIA special session at the JAMIT (Japanese Society of Medical Imaging Technology) Annual Meeting, 20th of July 2007, Tsukuba, Japan, organizers: Toshiharu Nakai & Daniel Racoceanu.
  14. Special Session - Medical Image Retrieval - AIRS 2006 – Asian Information Retrieval Symposium, 18 Oct. 2006, Singapore, organizers – D. Racoceanu IPAL France/Singapore, publications issued in Lecture Notes for Computer Science (LNCS)
  15. SFBI’06 - 1st Singaporean-French Biomedical Imaging workshop, 12-13 October 2006, Biopolis, Singapore, Organizing Committee Chairs: D. Racoceanu, Hugues Benoît-Cattin (CREATIS), organized by IPAL, SBIC (Singapore BioImaging Consortium), CREATIS/INSA Lyon, [SFBI 2006]

Oral communications without proceedings

  1. Racoceanu, D., Massive data in Digital Patholgy: insights about semantics/micro-semiology and scalable imaging methods, “Cycle de vie des images en microscopie : les enjeux techniques”, workshop organized by the CNRS with the networks CALCUL, DEVLOG, RBDD, RCCM, REMISOL, RTMFM, 15th of Dec. 2015, Paris, France.
  2. Ben Cheikh, B., Racoceanu, D., Graph-based mathematical morphology for the characterization of the spatial heterogeneity of tumours: A new approach for tumour growth modeling, workshop DYnamique et COntrôle des Croissances TUmorales, Rouen, France, 30th of Nov 2015.
  3. Ben Cheikh B., Berthaud P., Racoceanu D., Preliminary approach for crypt detection in Inflammatory Bowel Disease, Workshop du GDR ISIS (Information, Signal, Image et ViSion) – French CNRS scientific organization on Information, Signal, Image and Vision: Analyse de tissu biologique et histopathologie numérique, Paris, France, 23rd of June 2015.
  4. D. Racoceanu, Whole Slide Image exploration using a symbolic cognitive vision approach, Grenoble Interdisciplinary Days 2013, Health & ICT, Nanohealth and Devices, Septembre 26-27, 2013, University Grenoble Alpes, Grenoble, France.
  5. D. Racoceanu, High content biomedical image exploration using semantic, prior shapes and modelling/synthesis approaches, CNRS-NSTDA workshop, Mar. 12-13, 2013, Thailand.
  6. D. Racoceanu, Challenge of digital pathology: MICO (cognitive microscopy) experience project related to breast cancer grading, Workshop Bioimage Informatics, 23-24 Jan. 2013, Singapore.
  7. MICO ANR TecSan project consortium, Digital Histopathology, Breast Cancer and WSI Exploration, Catel 2011- communication Carrefour de la Télésanté, 20 Oct. 2011, Paris.
  8. D. Racoceanu, NUS & CNRS initiative at IPAL: Medical imaging joint researches related to Breast cancer grading and Intelligent vision system for neural stem cells tracking, 3rd NUS SoC – Vietnam Workshop, 4-5th March 2011, Hanoi University of Science & Technology, Hanoi, Vietnam.
  9. D. Racoceanu, IPAL-CNRS, the international joint laboratory initiative in Singapore, ICT’2010, EU-ASEAN Cooperation opportunities, Networking Session jointly organized by IPAL and SEACOOP, Bruxelles, Belgium, 27-29 September 2010.
  10. D. Racoceanu, Nicolas Loménie, IPAL overview - Image & Pervasive Access Lab, 7th ICT-Asia regional conférence, 15 & 16 March 2010, Keio University - Tokyo – Japan. [slides]
  11. N. Loménie, L. Roux, D. Racoceanu, Equipe Medical Image Understanding de l'IPAL, Unité Mixte Int. CNRS - France – Singapour, "MICO: plateforme de MIcroscopie virtuelle COgnitive", Imagerie pour la Biologie / Analyse et Traitement en Microscopie Fonctionnelle du Vivant, séminaire GdR ISIS - GdR Microscopie fonctionnelle du vivant, 16 Nov. 2009, Paris, France.
  12. A. Tutac, D. Racoceanu, Nicolas Loménie, Ludovic Roux, Didier Balensi and Thomas Putti, Knowledge Representation and Reasoning for Breast Cancer Grading in Cognitive Virtual Microscope Framework, A*STAR Scientific Conf. 2009, 28-29 Oct. 2009, Singapore.  [pdf]
  13. R. O. Teodorescu, Daniel Racoceanu, Ling Ling Chan, Prognosis of Parkinson's Disease, A*STAR Scientific Conference 2009, 28-29 Oct. 2009, Biopolis, Singapore. [pdf]
  14. A. Tutac, D. Racoceanu, N. Loménie, L. Roux, T. C. Putti and V. Cretu, “Breast Cancer Grading Knowledge Modeling and Reasoning for Cognitive Virtual Microscopy”, National Institutes of Health NIH Inter-Institute Workshop on Optical Diagnostic and Biophotonic Methods from Bench to Bedside, Bethesda, USA, 1- 2 Oct 2009.
  15. N. Loménie, Daniel Racoceanu, Medical Image Research Topics in relation to VPH EU framework, IPAL – Image & Pervasive Access Lab, 20th anniversary of ERCIM Meeting, the European Research Consortium for Informatics and Mathematics, 28 May 2009, Paris.
  16. D. Racoceanu, Breast cancer grading in a virtual microscope platform, Third ANR TecSan Franco-Taiwanese Biomedical Workshop, 27 March 2009, National Taiwan University, Taipei, Taiwan.
  17. D. Racoceanu, Content-based medical image retrieval and IPAL medical applications. State of the art and trends toward clinical application, 2009 France-Taiwan Seminar on Bilateral Cooperation in Health Technologies, 26 March 2009, National Kaohsiung University, Kaohsiung, Taiwan.  
  18. D. Racoceanu, A. Tutac, W. Xiong, J.-R. Dalle, C.-H. Huang, L. Roux, W.-K. Leow, A. Veillard, J.-H. Lim, T. Putti, T. Ming, A virtual microscope framework for breast cancer grading, A*STAR CCO workshop in Computer Aided Diagnosis, Treatment and Prediction, Biopolis, 15 Jan. 2009, Singapore.
  19. J.-R. Dalle, D. Racoceanu, W.-K. Leow, Contribution to an Automated Breast Cancer Grading System, First International Symposium on ICT for Health - ICT4Health 2008, 2008, Ateneo de Manila University, Manila, Philippines.
  20. P. Brezillon, Daniel Racoceanu, Contextualized diagnosis model: Example of the breast cancer, First International Symposium on ICT for Health - ICT4Health 2008, 2008, Ateneo de Manila University, Manila, Philippines.
  21. J. Liu, Joo Hwee Lim, Daniel Racoceanu, Wing Kee Damon Wong, Huiqi Li, Leaking detection for Medical image segmentation, First International Symposium on ICT For Health (ICT4Health 2008), 2008, Ateneo de Manila University, Manila, Philippines.
  22. S. Camarasu, Hugues Benoit-Cattin, Johan Montagnat, Daniel Racoceanu, Content-Based Medical Image Indexing and Retrieval on Grids, First International Symposium on ICT For Health - ICT4Health 2008, 2008, Manila, Philippines.
  23. P. Brezillon, Daniel Racoceanu, Contextual Approach in Image Processing. Application to cerebral MRI, ONCO-MEDIA – MIST’2007 workshop, International Medical Informatics Symposium in Taiwan, Hualien-Taipei, Wan-Fang Hospital, Taipei, Taiwan, Nov. 2007.  
  24. D. Racoceanu, ONtology and COntext related MEdical image Distributed Intelligent Access, first assessment of the project, the fifth ICT-Asia seminar, 18-19 november 2007, Taipei, Taiwan.
  25. D. Racoceanu, J.-R. Dalle, B. Qiu, L.-L. Chan, W.-K. Leow, J.-H. Lim, J. S. P. Tan, Knowledge Based Approach for Stroke Diagnosis, ONCO-MEDIA – MIST’2007 workshop, International Medical Informatics Symposium, Wan-Fang Hospital, Taipei, Taiwan, Nov. 2007.
  26. D. Racoceanu, C. Lacoste, J.-H. Lim, J.-P. Chevallet, X. Wei, Bridging the Semantic Gap using a UMLS Knowledge-based Medical Image Retrieval Approach; Application on CLEF Medical Image Database, 1st Singaporean-French Biomedical Workshop, 12-13 Oct. 2006, Singapore. [pdf]
  27. C. Lacoste, J.-P. Chevallet, J.-H. Lim, X. Wei, D. Racoceanu, D. Le Thi Hoang, R. Teodorescu, N. Vuillenemot, IPAL Knowledge-based Medical Image Retrieval in ImageCLEFmed 2006, Cross Language Evaluation Forum 2006 Int. Workshop, 20-22 Sept 2006, Alicante, Spain. [pdf]
  28. C. Lacoste, J.-P. Chevallet, J.-H. Lim, D. Racoceanu, Medical Image Retrieval based on Knowledge-Assisted Text and Image Indexing, SBIC – Singaporean Bio-Imaging Consortium Medical Imaging Workshop, 8 Aug. 2006, Singapore. [pdf]
  29. D. Racoceanu, Fusion text/image for medical case indexing, Fourth ICT-Asia ISERE Meeting: Inter-media Semantic Extraction & Reasoning, 5-7 juin 2006, Tokyo, Japan.
  30. D. Racoceanu, Content-Based Medical Image Retrieval – the Onco-Media project, TRUMA 2005: International Workshop on Task-Relevant Ubiquitous Media Access, associated with the Third ISERE Meeting: Inter-media Semantic Extraction & Reasoning, 18-20 Dec. 2005, Taipei, Taiwan.

Other Productions

- Patents and copyrights

  1. A 3 Dimensional Tracking Method for Time-lapse Suspension Cell and Cell sphere Image Acquisition using Phase Contrast Microscopy, US Patent Application filed Nov. 2012.
  2. A 3 Dimensional Tracking Method for Time-lapse Suspension Cell and Cell sphere Image Acquisition using Phase Contrast Microscopy, Singapore Patent Application filed Aug. 2011, ETPL ref: BII/P/06731/00/SG.
  3. PDFibAtl@s - System for detection and prognosis of the Parkinson’s Disease using MRI DTI information fusion - CNRS copyright DL 04137-01 the international research unit UMI2955, submitted on the 16th of December 2010, approved on the 13th of May 2011.
  4. HISTOGRAD - Virtual microscope for breast cancer grading CNRS copyright Dl 2944-01 for the international research unit UMI2955, Copyright granted in June 2009 (Dépôt APP - N° d'enregistrement : IDDN.fr.001.190019.000.S.P.2010.000.20900 en date du 14 Mai 2010).
  5. Dynamic real-time monitoring system, patent filled with Em@systec France, submitted in December 2008. (Brevet déposé à l’I.N.P.I. - France - 10 décembre 2008 numéro de demande 0858450, numéro1000043030, réf. 8 E50 BT FR 1 société Em@systec).

- National and Regional Communications and Disseminations

  1. D. Racoceanu, Singapore: Asia's Leading Location for Biomedical and Cosmetic Industries, Guest Editor's Note, Focus Magazine, French Chamber of Commerce Singapore, Jan.2014,pp.3 [pdf]
  2. IPAL Four more years for the French-Singaporean lab IPAL, CNRS International Magazine, No.22, July 2011. [link] [full magazine]
  3. Le laboratoire franco-singapourien poursuit son essor, Journal CNRS no256, May2011, pp.33 [link]
  4. IPAL: A Decade-Long Success Story, FCCS Focus Magazine, French Chamber of Commerce, Singapore, a Living Lab, summer 2010, pp. 22, 23 [pdf], [full magazine]
  5. Singapore, New Research Hub, Around the world, CNRS International Magazine, n°18, Jul 2010. [link]

- Miscellaneous

  1. IPAL in the success stories showcase (2011) of the SECAS EU project [success_stories] [about_SECAS_project] funded by the European Commission under the FP7 ICT program; SECAS is coordinated by Eutema, a research consultancy from Austria. Other partners include Optimat (UK), National ICT Australia (NICTA) and the Singapore Management University (SMU).