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Journal Article

  1. [ORKI-14]M. Orkisz, Hernández Hoyos, M., Pérez Romanello, V., Pérez Romanello, C., Prieto, J. C., and Revol-Muller, C., “Segmentation of the pulmonary vascular trees in 3D CT images using variational region-growing”, IRBM, vol. 35, pp. 11-19, 2014.
    https://www.sciencedirect.com/science/article/abs/pii/S1959031813001371?via%3Dihub
  2. [ROSE-10]J. L. Rose, Lalande, A., Bouchot, O., Bourennane, E. - B., Walker, P. M., Ugolini, P., Revol-Muller, C., Cartier, R., and Brunotte, F., “Influence of age and sex on aortic distensibility assessed by MRI in healthy subjects”, Magnetic Resonance Imaging, vol. 28, pp. 255 - 263, 2010.
    http://www.sciencedirect.com/science/article/B6T9D-4X1R2VB-3/2/92199cde38220b2ea8a2282c0b6d030f
  3. [GREN-05]T. Grenier, Revol-Muller, C., Costes, N., Janier, M., and Gimenez, G., “Automated seeds location for whole body NaF PET segmentation”, IEEE Trans Nucl Sci, vol. 52, pp. 1401 - 1405, 2005.
  4. [REVO-02b]C. Revol-Muller, Benoit-Cattin, H., Carillon, Y., Odet, C., Briguet, A., and Peyrin, F., “Bone MRI segmentation assessment based on synchrotron radiation computed microtomography”, IEEE Trans Nucl Sci, vol. 49, pp. 220–224, 2002.
  5. [REVO-02a]C. Revol-Muller, Peyrin, F., Carillon, Y., and Odet, C., “Automated 3D region growing algorithm based on an assessment function”, Pattern Recogn Lett, vol. 23, pp. 137–150, 2002.
  6. [REVO-97a]C. Revol-Muller and Jourlin, M., “A new minimum-variance region growing algorithm for image segmentation”, Pattern Recogn Lett, vol. 18, pp. 249-258, 1997.
  7. [JOUR-96]M. Jourlin, Bertrand, C., Coudert, J. L., Darsonville, F., Gremillets, P., Martinez, S., Pinolit, J. C., Revol-Muller, C., and Trunde, F., “3D imaging applications at the LISA laboratory during the last ten years”, Micr Microanal Microstruct, vol. 7, 1996.

Conference Paper

  1. [PRIE-12e]J. C. Prieto, Pérez Romanello, C., Pérez Romanello, V., Revol-Muller, C., Odet, C., Orkisz, M., and Hernández Hoyos, M., “Segmentación del árbol vascular pulmonar”, in XXXVIII Conferencia Latinoamericana en Informática (CLEI), Medellín, Colombia, 2012, pp. 1-7.
  2. [PRIET-12b]J. C. Prieto, Revol-Muller, C., Camelitti, P., and Odet, C., “Modeling 3D realistic organic tissues from 2D digital microscope images”, in ESMI "Hot Topics in molecular imaging” Topim'12, 2012, p. in press.
  3. [PACU-12a]A. Pacureanu, Langer, M., Revol-Muller, C., and Peyrin, F., “Imaging of the Bone Cell Network with Nanoscale Synchrotron Radiation Computed Tomography”, in SSBA 2012, Symposium on Image Analysis, Stockholm, Sweden, 2012.
  4. [PRIE-12a]J. C. Prieto, Revol-Muller, C., Peyrin, F., Camelitti, P., and Odet, C., “3D Texture synthesis for modeling realistic organic tissues”, in VISAPP 2012. International Conference on Computer Vision Theory and Applications, Rome, Italy, 2012, pp. 60-65.
  5. [REVO-12b]C. Revol-Muller, Grenier, T., Li, T., and Benoit-Cattin, H., “Feature Space Region Growing”, in International Conference on Image Processing, ICIP'12, Orlando, Florida, USA, 2012, p. in press.
  6. [REVO-12c]C. Revol-Muller, Rose, J. L., Pacureanu, A., Peyrin, F., and Odet, C., “Shape Prior in Variational Region Growing”, in International Conference on Image Processing Theory, Tools and Applications, IPTA'12, 2012, p. in press.
  7. [REVO-12a]C. Revol-Muller, Grenier, T., Rose, J. L., Pacureanu, A., Peyrin, F., and Odet, C., “Region Growing: Adolescence and adulthood ;Two visions of region growing: in feature space and variational framework”, in VISAPP 2012. International Conference on Computer Vision Theory and Applications, Rome, Italy, 2012, pp. 286-297.
  8. [PRIE-12c]J. C. Prieto, Revol-Muller, C., Odet, C., Orkisz, M., and Hernández Hoyos, M., “CreaLungs: a variational region growing method to segment pulmonary vascular trees”, in ISBI VESSEL12 Challenge, Barcelona, Spain, 2012.
    /site7/sites/www.creatis.insa-lyon.fr/files/AlgorithmDescription.pdf
  9. [PRIET-12d]J. C. Prieto, Mihaila, S., Hilaire, A., Fanton, L., Odet, C., and Revol-Muller, C., “Age estimation from 3D X-ray CT images of human fourth ribs”, in Worldcomp'12: 16th International Conference on Image Processing, Computer Vision, & Pattern Recognition IPCV'12, Las Vegas, Nevada, USA, 2012.
  10. [PACU-11]A. Pacureanu, Langer, M., Dong, P., Revol-Muller, C., Buzuloiu, V., and Peyrin, F., “Imagerie microscopique 3D du réseau lacuno-canaliculaire dans l’os humain”, in GRETSI, Bordeaux, 2011.
  11. [PACU-11]A. Pacureanu, Rollet, J., Revol-Muller, C., Buzuloiu, V., Langer, M., and Peyrin, F., “SEGMENTATION OF 3D CELLULAR NETWORKS FROM SR-MICRO-CT IMAGES”, in International Symposium on Biomedical Imaging, Chicago, USA, 2011.
  12. [UDOB-11]O. Udobata, Revol-Muller, C., and Lartizien, C., “Computer-aided tumor detection stemmed from the fuzzification of the Dempster-Shafer theory”, in SPIE Medical Imaging 2011: Computer-Aided Diagnosis, , Lake Buena Vista, Florida, United States, 2011, p. Proceedings Vol. 7963 .
  13. [PACU-10]A. Pacureanu, Revol-Muller, C., Rose, J. L., Sanchez-Ruiz, M., and Peyrin, F., “A Vesselness-guided Variational Segmentation of Cellular Networks from 3D Micro-CT”, in IEEE International Symposium on Biomedical Imaging (ISBI'10), Rotterdam, Netherlands, 2010, pp. 912 - 915.
  14. [ROSE-10a]J. L. Rose, Grenier, T., Revol-Muller, C., and Odet, C., “Unifying variational approach and region growing segmentation”, in 18th European Signal Processing Confernce (EUSIPCO-2010), Aalborg, Denmark, 2010, pp. 1781-1785.PDF icon [ROSE-10] unifying Variational Approach and Region growing Segmentation - Eusipco 2010.pdf (3.99 MB)
  15. [ALIX-10]T. Alix, Revol-Muller, C., H., C., C., B., M., B., P., S., and F., C., “Développement volumique et sagittal des sinus frontaux en fonction de l'angle C1/F1 crânio-adapté et de la classe squelettique. Etude à propos de 150 cas”, in Congrès national de stomatologie et chirurgie maxillo-faciale Paris octobre 2010, 2010.
  16. [PACU-09a]A. Pacureanu, Larrue, A., Peter, Z., Revol-Muller, C., Buzuloiu, V., and Peyrin, F., “Filtrage 3D non-linéaire pour la détection de microstructures biologiques à l'échelle nanométrique”, in XXIIe Colloque GRETSI - Traitement du Signal et des Images (GRETSI'09), Dijon, France, 2009, p. in-press.
  17. [ROSE-09b]J. L. Rose, Revol-Muller, C., Charpigny, D., and Odet, C., “Shape prior criterion based on Tchebichef moments in variational region growing”, in IEEE International Conference on Image Processing ICIP'09, Cairo, Egypt, 2009, p. in-press.
  18. [ROSE-09a]J. L. Rose, Revol-Muller, C., Reichert, C., and Odet, C., “Variational region growing”, in VISAPP-09 International Conference on Computer Vision Theory and Applications, Lisboa, Portugal, 2009, p. in-press.
  19. [ROSE-08b]J. L. Rose, Revol-Muller, C., Langlois, J. B., Janier, M., and Odet, C., “3D region growing integrating adaptive shape prior”, in Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on, Paris, France, 2008, pp. 967-970.
  20. [ROSE-07]J. L. Rose, Revol-Muller, C., Almajdub, M., Chereul, E., and Odet, C., “Shape Prior Integrated in an Automated 3D Region Growing method”, in IEEE International Conference on Image Processing ICIP'07, San Antonio, USA, 2007, pp. 53–56.
  21. [GREN-06a]T. Grenier, Revol-Muller, C., and Gimenez, G., “Hybrid approach for multiparametric mean shift filtering”, in ICIP'06, Atlanta, USA, 2006, pp. 1541-1544.
  22. [GREN-06b]T. Grenier, Revol-Muller, C., Costes, N., Janier, M., and Gimenez, G., “3D Robust Adaptive Region Growing for Segmenting [18F]fluoride Ion PET Images”, in 2006 NSS MIC, San Diego, USA, 2006, pp. 2644-2648.
  23. [GREN-05c]T. Grenier, Revol-Muller, C., Davignon, F., Basset, O., and Gimenez, G., “Multiparametric Smoothing Based On Mean Shift Procedure For Ultrasound Data Segmentation”, in EUSIPCO'05, Antalya, Turkey, 2005, p. Article ID cr1461, 4 pages.
  24. [GREN-05b]T. Grenier, Revol-Muller, C., Davignon, F., Basset, O., and Gimenez, G., “'Mean Shift' Adaptatif pour le lissage d'images ultrasonores”, in GRETSI'05, Louvain-La-Neuve, Belgium, 2005, pp. 53-56.
  25. [GREN-05a]T. Grenier, Revol-Muller, C., Davignon, F., Basset, O., and Gimenez, G., “Variable bandwidth Mean Shift for Smoothing ultrasonic images”, in EUSIPCO'05, Antalya, Turkey, 2005, p. Article ID cr1454, 4 pages.
  26. [DAVI-05]F. Davignon, Grenier, T., Revol-Muller, C., Gimenez, G., and Basset, O., “Lissage et segmentation d'images multi-paramétriques ultrasonores par une approche 'Mean shift'”, in GRETSI'05, Louvain-La-Neuve, Belgium, 2005, pp. 21-24.
  27. [GREN-03]T. Grenier, Revol-Muller, C., Costes, N., Janier, M., and Gimenez, G., “Automated seeds location for whole body NaF PET segmentation”, in IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference, Portland, OR, USA, 2003, pp. 2210-2214.
  28. [REVO-01b]C. Revol-Muller, Rombaut, M., and Janier, M., “Dempster-Shafer approach for high level data fusion applied to the assessment of myocardial viability”, in First International Workshop on Functional Imaging and Modeling of the Heart (FIMH'01), Helsinki, Finland, 2001, pp. 104–112.
  29. [ROMB-01]M. Rombaut, Revol-Muller, C., and Janier, M., “Modular fusion system for a computer-aided diagnosis of the myocardial viability”, in 4ème Conférence Internationale sur la Fusion d'Information, International Society for Information Fusion ISIF, Montréal, Canada, 2001.
  30. [REVO-01a]C. Revol-Muller, Rombaut, M., and Janier, M., “Une architecture de fusion modulaire pour l'assistance au diagnostic médical”, in GRETSI, Toulouse, France, 2001, pp. 140-143.
  31. [REVO-00b]C. Revol-Muller, Benoit-Cattin, H., Carillon, Y., Odet, C., Briguet, A., and Peyrin, F., “Bone MRI segmentation assessment based on synchrotron radiation computed microtomography”, in Nuclear Science Symposium and Medical Imaging Conference, Lyon, France, 2000, pp. 19.7-19.11.
  32. [REVO-00a]C. Revol-Muller, Peyrin, F., Odet, C., and Carillon, Y., “Automated 3D region growing algorithm governed by an evaluation function”, in IEEE International Conference on Image Processing ICIP'00, Vancouver, Canada, 2000.
  33. [REVO-97b]C. Revol-Muller, Jourlin, M., Fortin, T., and Coudert, J. L., “Algorithme de segmentation destiné aux images odontologiques tridimensionnelles”, in 37è Congrès de la Société Francophone de Chirurgie Buccale, Strasbourg, France, 1997.

Book Chapter

  1. [REVO-13]C. Revol-Muller, Grenier, T., Rose, J. L., Pacureanu, A., Peyrin, F., and Odet, C., “Region Growing: When Simplicity Meets Theory. Region growing revisited in feature space and variational framework”, in Lecture Notes Series of Communications in Computer and Information Science (CCIS), Springer-Verlag, vol. 359, 2013, pp. 426-444.

Invited Conference

  1. [PACU-12b]A. Pacureanu, Langer, M., Rose, J. L., Revol-Muller, C., and Peyrin, F., “3D nano-CT: a new approach for imaging at cellular scale”, General Assembly of the French Society for Signal and Image Processing in Life Sciences. 2012.
  2. [PEYR-00d]F. Peyrin, Revol-Muller, C., Carillon, Y., Martin-Badosa, E., Nuzzo, S., Bonnassie, A., and Briguet, A., “Synchrotron radiation Micro-CT : a reference tool for the characterization of bone samples”, Bone architecture and the competence of bone. Big Sur Symposium, USA, 2000.

HDR

  1. [REVO-12d]C. Revol-Muller, “Prise en compte de données multidimensionnelles et hétérogènes en imagerie médicale : contributions en fusion, filtrage et segmentation”. INSA Lyon, Lyon, 2012.
    Jury : Philippe Bolon (rapporteur), Mireille Garreau (rapporteur), Frédéric Truchetet (rapporteur), Olivier Basset, François Cotton, Françoise Peyrin, Christophe Odet

Thesis

  1. [REVO-96]C. Revol-Muller, “Méthodes de segmentation bidimensionnelles et tridimensionnelles appliquée à l'imagerie odontologique et biomédicale”, Université Jean Monnet, Saint Etienne, 1996.

Miscellaneous

  1. [PRIE-11]J. C. Prieto, Revol-Muller, C., and Odet, C., “Modélisation multiparamétrique d'organes basée sur le codage de la structure interne”, Journée Sciences Croisées Insa-Lyon: Modélisation et Sciences numériques. 2011.
  2. [REVO-10]C. Revol-Muller, Grenier, T., and Lartizien, C., “Architecture de fusion modulaire pour l'assistance au diagnostic médical”, Réunion des GDR STIC-SANTE Thème B: "Signaux et Images en santé" et GDR ISIS Thème B : "Image et Vision" GDR ISIS, Journée thématique commune : Avancées en fusion de données. 2010.
  3. [ODET-07]C. Odet, Rose, J. L., and Revol-Muller, C., “Synthèse générale des méthodes de segmentation intégrant de l'a priori géométrique ”, Réunion des GDR STIC-SANTE Thème B: "Signaux et Images en santé" et GDR ISIS Thème B : "Image et Vision", Journée thématique commune: "Segmentation de structures anatomiques avec intégration d’a priori géométrique". 2007.
  4. [GREN-06c]T. Grenier, Revol-Muller, C., Costes, N., Janier, M., and Gimenez, G., “3D robust adaptive region growing for segmenting PET images”, 1st Singaporean-French Biomedical Imaging Workshop, 2006. 2006.
  5. [REVO-93]C. Revol-Muller, Pachod, V., and Jourlin, M., “Contrôle de pièces sur convoyeur”, Colloque Imagicad 93 : Utilisations industrielles de la vision assistée par ordinateur. Lyon, 1993.
  6. [REVO-93]C. Revol-Muller, Pachod, V., and Jourlin, M., “Pilotage d'un convoyeur industriel et contrôle des pièces par vision”, Assemblée générale du Comité Scientifique et Technique du Pôle Productique Rhône-Alpes. Annecy, 1993.

Software

  1. [REVO-97]C. Revol-Muller and Muller, L., “PDS84 :PIC 16C84 Development System”, Revue d’électronique Elektor, 8ème prix au « concours international : microprocesseurs 1997. 1997.