1. [ZHU-01] Y. M. Zhu, V. Kaftandjian, and D. Babot. Chapitre 8 : X-ray imaging and weld inspection using data fusion. In Applications of NDT data fusion, pages 159-191. . Kluwer Academic, Publ., 2001.

1. [FRIN-10] C. Frindel, M. Robini, P. Croisille, and Y. M. Zhu. A graph-based approach for automatic cardiac tractography. Magn Reson Med, 64(4):1215-1229, 2010.



2. [BAO-09] L.J. Bao, Y.M. Zhu, W.Y. Liu, P. Croisille, Z.B. Pu, M. Robini, and I.E. Magnin. Denoising of human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation. Phys Med Biol, 54:1435-1456, 2009.



3. [BERK-09] M. Berkane, P. Clarysse, J. Yankam Njiwa, Y-M. Zhu, and I. E. Magnin. Spatio-temporal summarizing method of periodic image sequences with Kohonen Maps. Neural Network World, pp (in press), 2009.



4. [FRIN-09] C. Frindel, M. Robini, P. Croisille, and Y. M. Zhu. Comparison of regularization methods for human cardiac diffusion tensor MRI. Med Image Anal, 13:405-418, 2009.



5. [LUO-09b] J.H. Luo and Y.M. Zhu. Image Reconstruction Scheme Based on Phase Correction and Singularity Function Analysis Model. J Signal Proces Syst, 54:79-88, 2009.



6. [LUO-09a] J.H. Luo, Y.M. Zhu, and I.E. Magnin. Denoising by Averaging Reconstructed Images: Application to Magnetic Resonance Images. IEEE Trans Biomed Eng, 56(3):666-674, 2009.



7. [QIN-09] H.X. Qin, J. Yang, and Y.M. Zhu. A Feature-Preserving Filtering Approach for Point Set Surface and Surface Attributes Based on Robust Statistics. J Inf Sci Eng, pp in-press, 2009.



8. [XIE-09b] K. Xie and Y.M. Zhu. Classification of Brain Tumors using kurtosis of the DCT Data. Eur J Radiol, pp in-press, 2009.



9. [XIE-09a] K. Xie and Y.M. Zhu. Interactive Surgery Simulation for the Nose Augmentation Using CT Data. Neural Comput Appl, pp in-press, 2009.



10. [XIN-09] H.M. Xin and Y.M. Zhu. Multiple information-based spot matching method for two-dimensional gel electrophoresis images. Electrophoresis, pp in-press, 2009.



11. [LIU-08] W.Y. Liu, Z.J. Tang, Y.M. Zhu, W.H. Liu, S. Hu, Y.L. Zhang, L.H. Wang, and I.E. Magnin. Novel data enhancement technology for ultrasonic stereovision. Optics and Precision Engineering, 16:1759-1766, 2008.



12. [LUO-08] J.H. Luo, Y.M. Zhu, and I.E. Magnin. Phase correction based singularity function analysis for partial k-space reconstruction. Magn Reson Imaging, 26:(746-753), 2008.



13. [QIN-08a] H.X. Qin, J. Yang, and Y.M. Zhu. A Novel Meshless Method for Point Set Surface Processing. Optical Engineering, 47, 2008.



14. [QIN-08b] H.X. Qin, J. Yang, and Y.M. Zhu. Nonuniform Bilateral filtering for Point Sets and Surface Attributes. The Visual Computer-International Journal of Computer Graphics, 24:1067-1074, 2008.



15. [XIE-08c] K. Xie, S. Yang, and Y.M. Zhu. High-Quality Multi-resolution Volume Rendering Based on Medical Dataset. Sciencepaper Online, June, 2008.



16. [XIE-08a] K. Xie, J. Yang, and Y.M. Zhu. Real-time visualization of large volume datasets on standard PC hardware. Comput Meth Prog Bio, 90:117-123, 2008.



17. [XIE-08b] K. Xie, J. Yang, and Y.M. Zhu. The 3D Cutting Algorithm Based on Surface Reconstruction. Sciencepaper Online, June, 2008.



18. [MIAO-07] P. Miao, B. Hiba, J.H. Luo, D. Sappey-Marinier, I.E. Magnin, and Y.M. Zhu. MR image reconstruction from partial k-space using singularity function representations. Comput Med Imag Graph, 571:239-242, 2007.



19. [MILL-07] J Milles, Y.M. Zhu, G. Gimenez, C.R.G. Guttmann, and I.E. Magnin. MRI intensity nonuniformity correction using simultaneously spatial and gray-level histogram information. Comput Med Imag Graph, 31:81-90, 2007.



20. [XIE-07a] K. Xie, J. Yang, and and Y.M. Zhu. Fast collision detection based on nose augmentation virtual surgery. Comput Meth Prog Bio, 88:1-7, 2007.



21. [XIE-07c] K. Xie, J. Yang, and Y.M. Zhu. Interactive volume cutting of medical data. Comput Biol Med, 37:1155-1159, 2007.



22. [XIE-07b] K. Xie, J. Yang, and Y.M. Zhu. Real time volume rendering of large datasets on standard PC hardware. Computer Applications, 27:1129-1131, 2007.



23. [YANK-07] J. Yankam-Njiwa, Y.M. Zhu, M. Robini, and I.E. Magnin. Magnetic resonance image reconstruction analytic image representation. Nucl Instr Meth Phys Res A, 571(1-2):73-76, 2007.



24. [BELA-06] B. Belaroussi, J. Milles, S. Carme, Y.M. Zhu, and H. Benoit-Cattin. Intensity non-uniformity correction in MRI: Existing methods and their validation. Med Image Anal, 10:234-246, 2006.



25. [LI-06] X.L. Li, J. Yang, K. Xie, and Y.M. Zhu. High Quality Rendering with Depth Cueing of Volumetric Data Using Monte Carlo Integration. Comput Biol Med, 36(9):1014-1025, 2006.



26. [LI-06a] X.L. Li, J. Yang, and Y.M. Zhu. Combining Estimators for Monte Carlo Volume Rendering with Shading. Visual Comput, 22:468-477, 2006.



27. [LI-06b] X.L. Li, J. Yang, and Y.M. Zhu. DRR generation by an adaptive Monte Carlo method. Phys Med Biol, 51(11):2745-2752, 2006.



28. [MILL-06] J. Milles, Y.M. Zhu, N. Chen, L. Panych, G. Gimenez, and C.R.G. Guttmann. Computation of Transmitted and Received B1 Fields in Magnetic Resonance Imaging. IEEE Trans Biomed Engin, 53(5):885-895, 2006.



29. [YU-06] Z.Q. Yu, Y. Zhu, J. Yang, and Y.M. Zhu. Hybrid Region-Boundary Model for Cerebral Cortical Segmentation in MRI. Comput Med Imag Grap, 30:197-208, 2006.



30. [KAFT-05] V. Kaftandjian, Y.M. Zhu, O. Dupuis, and D. Babot. The combined use of the evidence theory and fuzzy logic for improving multimodal non destructive testing systems. IEEE Trans Instr Measur, 54(5):1968-1977, 2005.



31. [LUO-05] J. Luo, Y.M. Zhu, P. Clarysse, and I.E. Magnin. Correction of Bias Field in MR Images Using Singularity Function Analysis. IEEE Trans Med Imaging, 24(8):1067-1085, 2005.



32. [XIE-05b] K. Xie, J. Yang, and Y.M. Zhu. Real-time rendering of 3D medical data sets. Future Generation Computer Systems, 21(4):573-581, 2005.



33. [XIE-05c] K. Xie, J. Yang, and Y.M. Zhu. Semi-automated brain tumor and edema segmentation using MRI. Eur J Radiol, 56(1):12-19, 2005.



34. [XIE-05] K. Xie, J. Yang, Y.M. Zhu, and X.L. Li. HVS-Based medical image compression. Eur J Radiol, 55(1):139-145, 2005.



35. [ZHAO-05] J. Zhao, Y.M. Zhu, P.M. Sing, Q. Fan, and J.H. Luo. Recognition of gene acceptor site based on multi-objective optimization. Acta Biochim Biophys Sin, 37(7):435-439, 2005.



36. [LUO-04] J.H. Luo and Y.M. Zhu. MR Image reconstruction from truncated k-space using a layer singular point extraction technique. IEEE Trans Nucl Sci, 51(1):157-169, 2004.



37. [ZHOU-04] L.Q. Zhou, Y.M. Zhu, J. Grimaud, M. Hermier, M. Rovaris, and M. Filippi. A new method for analyzing histograms of brain magnetization transfer ratios: comparison with existing techniques. Am J Neuro Radiol, 25(7):1234-1241, 2004.



38. [KAFT-03] V. Kaftandjian, O. Dupuis, D. Babot, and Y.M. Zhu. Uncertainty modelling using Dempster-Shafer theory for improving detection of weld defects. Pattern Recogn Lett, 24:547-564, 2003.



39. [GRIM-02b] J. Grimaud, L.Q. Zhou, and Y.M. Zhu. Application de l'IRM par transfert d'aimantation à l'étude de la sclérose en plaques. Rev Neurol, 158(12):1157-1173, 2002.



40. [GRIM-02a] J. Grimaud, Y.M. Zhu, and M. Rombaut. Les techniques d'analyse quantitative des IRM cérébrales : application à la sclérose en plaques. Rev Neurol, 158(3):381-389, 2002.



41. [ROMB-02] M. Rombaut and Y.M. Zhu. Study of Dempster-Shafer theory for image segmentation applications. Image Vision Comput, 20(1):15-23, 2002.



42. [ZHU-02a] Y.M. Zhu, L. Bentabet, O. Dupuis, V. Kaftandjian, D. Babot, and M. Rombaut. Automatic determination of mass functions in Dempster-Shafer theory using fuzzy C-Means and spatial neighbourhood information for image segmentation. Optical Engineering, 41(04):760-770, 2002.



43. [ZHOU-01] L.Q. Zhou, Y.M. Zhu, C. Bergot, A.M. Laval-Jeantet, V. Bousson, J. D. Laredo, and M. Laval-Jeantet. A method of Radio-Frequency inhomogeneity correction for tissue classification in brain MRI. Comput Med Imag Grap, 25:379-389, 2001.



44. [BOUD-00] A. Boudraa, S.M.R. Dehak, Y.M. Zhu, C. Pachai, Y. G. Bao, and J. Grimaud. Automated segmentation of multiple sclerosis lesions in multispectral MRI using fuzzy clustering. Comput Biol Med, 30(1):23-40, 2000.



45. [DUPU-99a] O. Dupuis, V. Kaftandjian, D. Babot, and Y.M. Zhu. Automatic detection and characterisation of weld defects : determination of confidence levels for data fusion of radioscopic and ultrasonic images. Brit Inst NDT, 41(3):170-172, 1999.



46. [DROM-98] A. Dromigny, Y.M. Zhu, I.E. Magnin, and D. Revel. Fusion of Cine-MR and contrast-enhanced first-pass MR data in patients with coronary artery disease : a feasability study. Invest Radiol, 33(1):12-21, 1998.



47. [DUPO-98] F. Dupont, Y.M. Zhu, J. Grimaud, C. Odet, C. Confavreux, and J.C. Froment. Utilisation de la distribution de Wigner-Ville 2D pour la segmentation des lésions de Sclérose En Plaques en IRM. Innov Tech Biol Med, 19(3):229-236, 1998.



48. [PACH-98a] C. Pachai, Y.M. Zhu, J. Grimaud, M. Hermier, A. Dromigny-Badin, A. Boudraa, G. Gimenez, C. Confavreux, and J.C. Froment. A pyramidal approach for automatic segmentation of multiple sclerosis lesions in brain MRI. Comput Med Imag Grap, 22:399-408, 1998.



49. [DROM-97] A. Dromigny and Y.M. Zhu. Improving the dynamic range of Real-time X-Ray imaging systems via bayesian fusion. J Nondestr Eval, 16(2):147-168, 1997.



50. [DROM-97a] A. Dromigny-Badin, S. Rossato, and Y.M. Zhu. Fusion de données radioscopiques et ultrasonores via la théorie de l'évidence. Traitement du Signal, 14(5):499-510, 1997.



51. [PACH-97c] C. Pachai, Y.M. Zhu, J. Grimaud, M. Hermier, A. Dromigny-Badin, T. Siberil, G. Gimenez, J.C. Froment, and C. Confavreux. Automatic segmentation of multiple sclerosis lesions in 2D MRI data. M S Journal, 3(5):336, 1997.



52. [KAFT-96d] V. Kaftandjian, Y.M. Zhu, G. Peix, and D. Babot. Automatic recognition of defects inside aluminium lingots by X-Ray imaging. Brit Inst NDT, 38(9):618-625, 1996.



53. [KAFT-96a] V. Kaftandjian, Y.M. Zhu, G. Peix, and D. Babot. Contrast transfer function measurement of X-ray solid-state linear detectors using bar/space pattern methods. Non-Destruct Test Eval, 29(1):3-11, 1996.



54. [KAFT-96b] V. Kaftandjian, Y.M. Zhu, G. Rozière, G. Peix, and D. Babot. A comparison of the ball, wire, edge and bar/space pattern techniques for modulation transfer function measurements of linear X-ray detectors. J X Ray Sc Technol, 6:205-221, 1996.



55. [ZHU-95c] Y.M. Zhu and R. Goutte. A comparison of bilinear space/spatial-frequency representations for texture discrimination. Pattern Recogn Lett, 16:1057-1068, 1995.



56. [ZHU-95a] Y.M. Zhu and R. Goutte. Analysis and comparison of space/spatial-frequency and multiscale methods for texture segmentation. Optical Engineering, 34(1):269-282, 1995.



57. [ZHU-95b] Y.M. Zhu, V. Kaftandjian, G. Peix, and D. Babot. Modulation transfer function evaluation of linear solid state X-ray sensitive detectors using edge techniques. Appl Opt, 34(22):4937-4943, 1995.



58. [ZHU-93a] Y.M. Zhu, R. Goutte, and M. Amiel. On the use of two-dimensional Wigner-Ville distribution for texture segmentation. Signal Proces, 30(3):329-353, 1993.



59. [ZHU-92a] Y.M. Zhu, F. Peyrin, R. Goutte, and M. Amiel. Analyse spectrale locale de l'image par transformation de Wigner-Ville. Traitement du Signal, 9(3):281-289, 1992.



60. [ZHU-91a] Y.M. Zhu, F. Peyrin, and R. Goutte. Sur la transformation de pseudo-Wigner-Ville discrète en temps et en fréquence. Ann Télécom, 46(5 6):301-309, 1991.

1. [CAST-10] Christopher Casta, Patrick Clarysse, Jérôme Pousin, Joël Schaerer, Pierre Croisille, and Yue-Min Zhu. Incorporating low-level constraints for the retrieval of personalised heart models from dynamic MRI. In Statistical Atlases and Computational Models of the Heart: Mapping Structure and Function (STACOM), MICCAI 2010 Workshop, volume LNCS 6364, pages 174-183, 2010. Springer-Verlag Berlin Heidelberg.



2. [BAO-09b] L.J. Bao, W.Y. Liu, Z.B. Pu, L. Fanton, S. Rapacchi, P. Croisille, Y.M. Zhu, and I.E. Magnin. Sparse representation based MRI denoising with total variation. In IEEE ICSP'08, Tianjin, China, pages in press, 2009.



3. [FRIN-09b] C. Frindel, M. Robini, P. Croisille, and Y.M. Zhu. Cardiac Fibre Trace Clustering for the interpretation of the Human Heart Architecture. In Proc. 4th Int. Conf. FIMH, Nice, France, pages 39-48, June 2009.



4. [FRIN-09c] C. Frindel, M. Robini, P. Croisille, and Y.-M. Zhu. Improved global cardiac tractography by simulated annealing. In Proc. 16th Int. Conf. IEEE ICIP, Cairo, Egypt, pages 813-816, November 2009.



5. [ROBI-09] M. Robini, P.-J. Viverge, Y.-M. Zhu, and I.E. Magnin. Edge-preserving image reconstruction with wavelet-domain edge continuation. In Proc. 6th Int. Conf. Image Analysis and Recognition, Halifax, Canada, pages 13-22, July 2009.



6. [YANK-09] J. Yankam Njiwa, M. Berkane, J.H. Luo, P. Clarysse, I.E. Magnin, and Y.M. Zhu. Reconstruction of cardiac Cine MR Images using analytic image and neural networks. In ISPA'09, Salzburg, Austria, pages in-press, 2009.



7. [BAO-08] L.J. Bao, W.Y. Liu, Y.M. Zhu, B.P. Zhao, and I.E. Magnin. Analysis of cardiac diffusion tensor magnetic resonance images using sparse representation. In Proc. 29th Int. Conf. IEEE EMBS, Beijing, China, pages 2154-2157, 2008.



8. [FRIN-08] C. Frindel, P. Gueth, P. Clarysse, Y.M. Zhu, and M. Robini. A global approach to cardiac tractography. In Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on, pages 883-886, May 2008.



9. [XIN-08] H.M Xin, Y.M. Zhu, and R. Goutte. Investigation of the role of spot pattern information in two-dimensional gel electrophoresis image registration. In Signal Processing; ICSP'2008, Beigin par Beijing, R.P. China, pages 72170-2173, 2008.



10. [BAO-07] L. Bao, Y.M. Zhu, W.Y. Liu, M. Robini, Z. Pu, and I.E. Magnin. Analysis of cardiac diffusion tensor magnetic resonance images using sparse representation. In Proc. 29th Int. Conf. IEEE EMBS, Lyon, France, pages 4516-4519, 2007.



11. [FRIN-07] C. Frindel, M. Robini, S. Rapacchi, E. Stephant, Y.M. Zhu, and P. Croisille. Towards in vivo diffusion tensor MRI on human heart using edge-preserving regularization. In Proc. 29th Int. Conf. IEEE EMBS, Lyon, France, pages 6007-6010, 2007.



12. [LIU-07] W.Y. Liu, Y.L. Zhang, W.H. Liu, S. Hu, Y.M. Zhu, and I.E. Magnin. A robust algorithm based on nonstationary degree for ultrasonic data enhancement. In IEEE Int. Conf. on Systems, Man and Cybernetics, Montreal, Que., Canada, pages 1061-1066, 2007.



13. [YANK-07a] J. Yankam-Njiwa, B. Hiba, and Y.M. Zhu. Cardiac Cine MR Reconstruction From Partial k-Space Using the Notion of Analytic Image. In Conf Proc IEEE Eng Med Biol Soc, volume 2007, Lyon, France, pages 2057-2060, August 2007.



14. [YANK-06b] J. Yankam-Njiwa, Y.M. Zhu, J. Liou, and I.E. Magnin. Image reconstruction from partial k-space using the notion of analytic image. In 8th International Conference on Signal Processing (ICSP), Guilin, R.P. China, pages 994-997, November 2006.



15. [NJIWA-06] J. Yankam-Njiwa, Y.M. Zhu, M. Robini, J.H. Luo, and I.E. Magnin. Image reconstruction from partial k-space using the notion of analytic image. In Int. Conf. Signal Processing, Guilin, R.P. China, pages 994-997, 2006.



16. [YANK-06a] J. Yankam-Njiwa, Y.M. Zhu, M. Robini, and I.E. Magnin. Magnetic resonance image reconstruction using the notion of analytic image. In EUROMEDIM Conference(Euromedim 2006), Marseille, France, pages 73-76, May 2006.



17. [CHEN-05] L.S. Cheng, J. Yang, X. Fan, and Y.M. Zhu. A Generalized Level Set Formulation of the Mumford-Shah Functional for Brain MR Image Segmentation. In Information Processing in Medical Imaging (IPMI'05), Colorado, USA, pages 418-430, 2005.



18. [XIE-05c] K. Xie, J. Yang, and Y.M. Zhu. Multi-resolution LOD Volume Rendering In Medicine. In The International Conference on Computational Science, Some City, Some Country, pages 925-932, 2005.



19. [MILL-04c] J. Milles and Y.M. Zhu. Model-Based Intensity Nonuniformity Correction in Brain MRI. In IEEE CIE 7th International Conference on Signal Processing, Beijing, P.R. China, 2004.



20. [MILL-04b] J. Milles, Y.M. Zhu, N. Chen, L. Panych, G. Gimenez, R.G. Charles, and C. Guttmann. MRI intensity inhomogeneity correction using simultaneously spatial and gray-level histogram information. In SPIE Medical Imaging, volume 5370, San Diego (California, USA), pages 734-742, 2004.



21. [MILL-03] J. Milles, Y.M. Zhu, N. Chen, L. Panych, G. Gimenez, and C.R.G. Guttman. Computation of transmitted and received B1 fields in magnetic resonance imaging. In CARS 2003 Computer Assisted Radiology and Surgery-17th International Congress and Exhibition, London, UK, pages 1323, 2003.



22. [ZHU-03] Y. M. Zhu, J.H. Luo, P. Clarysse, and I.E. Magnin. Correction des inhomogénéités d'intensité en IRM. In Conférences F. Lhermitte - 13e Rendez-Vous de l'ARSEP, Paris, France, pages 35, 2003.



23. [GANN-02] M. Ganna, M. Rombaut, R. Goutte, and Y.M. Zhu. Improvement of brain lesions detection using information fusion approach. In IEEE CIE - International Conference on Signal Processing, Beijing, P.R. China, pages 4, 2002.



24. [MILL-02a] J. Milles, Y.M. Zhu, G. Gimenez, and C.R.G. Guttman. Correction des inhomogénéités d'intensité en IRM. In Conférences F. Lhermitte - 12e Rendez-Vous de l'ARSEP, Paris, France, pages 16-17, 2002.



25. [ZHU-02b] Y.M. Zhu, J. Grimaud, L.Q. Zhou, M. Filippi, and M. Rovaris. Comparative study of different brain MTR parameters for the study of multiple sclerosis. In 6 Congress of the European Federation of Neurological Societies, Vienna, Austria, pages 131, 2002.



26. [PACH-01] C. Pachai, Y.M. Zhu, C. Guttmann, R. Kikinis, F.A. Jolesz, G. Gimenez, J.C. Froment, C. Confavreux, and S.K. Warfield. Unsupervised and adaptive segmentation of multispectral 3D magnetic resonance images of human brain : a generic approach. In Fourth International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI'01), Utrecht, The Netherlands, pages 1067-1074, 2001.



27. [BENT-00b] L. Bentabet, Y.M. Zhu, O. Dupuis, V. Kaftandjian, D. Babot, and M. Rombaut. Use of fuzzy clustering for determining mass functions in Dempster-Shafer theory. In 16th IFIP World Computer Congress & Fifth International Conference on Signal Processing, Beijing, P.R. China, pages 1462-1470, 2000.



28. [LUO-00] J. H. Luo, S. Hao, and Y.M. Zhu. Layer extraction technique applied to edge detection of MR images with truncation artifacts. In IEEE Nuclear Science Symposium and Medical Imaging Conference, Lyon, France, pages 15.259-15.262, 2000.



29. [PACH-00c] C. Pachai, S.K. Warfield, Y.M. Zhu, C. Guttmann, J.C. Froment, and C. Confavreux. Automatic quantification of brain atrophy in MS using millimetric T1-weighted MRI. In ECTRIMS, Toulouse, France, 2000.



30. [PACH-00b] C. Pachai, Y.M. Zhu, C. Guttmann, J. Grimaud, M. Hermier, G. Gimenez, C. Confavreux, and J.C. Froment. L Unsupervised, adaptative, 3D Segmentation of brain tissues in multispectral MRI : application to quantification of multiple sclerosis lesions. In 10th Meeting of the European Neurological Society, Jerusalem, Israel, pages 820, 2000.



31. [ZHOU-00] L. Q. Zhou, Y.M. Zhu, J. Grimaud, G. Gimenez, M. Hermier, and J.C. Froment. Analyse par histogramme du transfert d'aimantation pour l'étude de la sclérose en plaques. In Conférences F. Lhermitte - 9e Rendez-Vous de l'ARSEP, Paris, France, pages 41-42, 2000.



32. [BENT-99] L. Bentabet, Y.M. Zhu, J. Grimaud, A. Boudraa, M. Hermier, G. Gimenez, J.C. Froment, and C. Confavreux. The combined use of FCM and evidence theory for segmentation of MS lesions in MRI. In 15th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS'99), volume 5, Basel, Switzerland, pages 56, 1999.



33. [DUPU-99b] O. Dupuis, V. Kaftandjian, Y.M. Zhu, and D. Babot. Détection de défauts par fusion de signaux ultrasonores et d'images radiographiques. In 17e Colloque GRETSI, Vanne, France, pages 1045-1048, 1999.



34. [PACH-99] C. Pachai, Y.M. Zhu, C. Guttmann, J. Grimaud, M. Hermier, G. Gimenez, J.C. Froment, and C. Confavreux. Segmentation 3D, non supervisée et adaptative des tissus cérébraux en IRM multispectrale : application à la détection des lésions de SEP. In Conférences F. Lhermitte-9e Rendez-Vous de l'ARSEP, Paris, France, pages 47, 1999.



35. [ZHU-99a] Y.M. Zhu, J. Grimaud, F. Reynaud, C. Pachai, M. Hermier, G. Gimenez, J.C. Froment, and C. Confavreux. Segmentation of brain magnetic resonance images using the multiscale contour approach. In 15th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS'99), volume 5, Basel, Switzerland, pages 56, 1999.



36. [BOUD-98a] A. Boudraa, Y.M. Zhu, S.M.R. Dehak, J. Grimaud, C. Pachai, A. Dromigny-Badin, M. Hermier, Y.G. Bao, G. Gimenez, J.C. Froment, and C. Confavreux. Segmentation automatique des lésions de sclérose en plaques en IRM par la logique floue. In Journées de Neurologie de Langue Française, Paris, France, pages 1S45-44, 1998.



37. [DROM-98c] A. Dromigny-Badin, Y.M. Zhu, G. Gimenez, and R. Goutte. Image segmentation through using the evidence theory based data fusion technique. In IEEE CIE International Conference on Signal Processing, Beijing, P.R. China, pages 994-997, 1998.



38. [DROM-98a] A. Dromigny-Badin, Y.M. Zhu, J. Grimaud, C. Pachai, A. Boudraa, M. Hermier, G. Gimenez, J.C. Froment, and C. Confavreux. Use of data fusion technique for the automated segmentation of multiple sclerosis lesions in magnetic resonance images. In Eighth Meeting of the European Neurological Society, Nice, France, pages 446, 1998.



39. [DROM-98b] A. Dromigny-Badin, Y.M. Zhu, C. Pachai, Y.G. Bao, J. Grimaud, M. Hermier, A. Boudraa, G. Gimenez, J.C. Froment, and C. Confavreux. Développement d'un logiciel de détection et de quantification automatiques des lésions cérébrales de sclérose en plaques en IRM. In Xème Réunion Annuelle de la Société Franco-Romande de Neurologie, Lyon, France, 1998.



40. [PACH-98b] C. Pachai, Y.M. Zhu, C. Guttmann, J. Grimaud, M. Hermier, G. Gimenez, J.C. Froment, and C. Confavreux. MS-TRACKER : validation à grande échelle d'un algorithme de détection automatique de la cavité intra-crânienne en IRM conventionnelle. In V Conférences F.-Lhermitte, 8e Rendez-Vous de l'ARSEP, Paris, France, pages 23-24, 1998.



41. [DROM-97b] A. Dromigny-Badin and Y.M. Zhu. Fusion de données complémentaires en vue de l'amélioration de la dynamique des systèmes d'imagerie. In GRETSI'97, Grenoble, France, pages 1415-1418, 1997.



42. [DROM-97d] A. Dromigny-Badin, Y.M. Zhu, C. Pachai, M. Hermier, J. Grimaud, G. Gimenez, J.C. Froment, and C. Confavreux. Segmentation of MS Lesions using evidence theory, Multiple Sclerosis. In 13th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS,97), volume 13, Istanbul, Turkey, pages 336, 1997.



43. [DROM-97c] A. Dromigny-Badin, Y.M. Zhu, C. Pachai, M. Hermier, J. Grimaud, G. Gimenez, J.C. Froment, and C. Confavreux. Segmentation of Multiple sclerosis lesions through fusion of multispectral magnetic resonance brain images. In World Congress on Medical Physics and Biomedical Engineering, Nice, France, pages 722, 1997.



44. [DUPO-97c] F. Dupont, C. Odet, and Y.M. Zhu. Control of flat steel products by texture segmentation in the Wigner-Ville domain. In Quality control by Artificial Vision (QCAV'97), Clermont-Ferrand, France, pages 225-230, 1997.



45. [PACH-97b] C. Pachai, Y.M. Zhu, J. Grimaud, M. Hermier, A. Dromigny-Badin, A. Boudraa, G. Gimenez, J.C. Froment, and C. Confavreux. MS-TRACKER : un logiciel d'analyse et de quantification automatiques des lésions de sclérose en plaques en IRM conventionelle. In Les 7èmes Rendez-Vous de l'ARSEP, Paris, France, pages 15-16, 1997.



46. [PACH-97d] C. Pachai, Y.M. Zhu, J. Grimaud, M. Hermier, A. Dromigny-Badin, T. Siberil, G. Gimenez, C. Confavreux, and J.C. Froment. A multiresolution approach for automatic segmentation of multiple sclerosis lesions in conventional 2D MRI data. In World Congress on Medical Physics and Biomedical Engineering, Nice, France, pages 724, 1997.



47. [PACH-97a] C. Pachai, Y.M. Zhu, J. Grimaud, M. Hermier, A. Dromigny-Badin, T. Siberil, G. Gimenez, J.C. Froment, and C. Confavreux. Automatic segmentation of multiple sclerosis lesions in 2D MRI data. In 13th Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS,97), volume 3, Istanbul, Turkey, pages 338, 1997.



48. [DROM-96] A. Dromigny-Badin and Y.M. Zhu. Amélioration de la dynamique des systèmes d'imagerie à rayons X par fusion bayésienne. In Journées Thématiques du GdR ISIS en Fusion d'Informations, Paris, France, pages 40-44, 1996.



49. [DUPO-96] F. Dupont, Y.M. Zhu, C. Odet, and R. Goutte. Texture classification in the Wigner-Ville domain. In 3th International Conference on Signal Processing ICSP'96, Beijing, P.R. China, pages 327-330, 1996.



50. [KARO-96] B. Karoubi, Y.M. Zhu, G. Gimenez, and J. Bigun. Detection of objects in RF ultrasonic images using 2-D spatial phase techniques. In IEEE international Conference on Image Processing, volume 1, Lausanne, Suisse, pages 641-644, 1996.



51. [MAGN-96a] I.E. Magnin, G. Rochard, Y.M. Zhu, G. Gimenez, C. Confavreux, and J.C. Froment. Détection automatique des lésions encéphaliques de sclérose en plaques en IRM par approche pyramidale. In Les Rendez-vous de l'ARSEP, Paris, France, 20 Février 1996.



52. [PACH-96] C. Pachai, Y.M. Zhu, G. Gimenez, J.C. Froment, M. Hermier, C. Confavreux, and J. Grimaud. Segmentation et quantification automatiques des lésions de sclérose en plaques en IRM. In Les 6èmes Rendez-Vous de l'ARSEP, 10 décembre 1996, Paris, France, pages 12, 1996.



53. [ROSS-96] S. Rossato, A. Dromigny-Badin, Y.M. Zhu, V. Kaftandjian, C. Odet, P. Guy, Y. Jayet, G. Peix, and G. Gimenez. Amélioration de la fiabilité du contrôle non destructif par fusion de données radioscopiques et ultrasonores. In Journées Thématiques du GdR ISIS en Fusion d'Informations, Paris, France, pages 54-58, 1996.



54. [ZHU-94] Y.M. Zhu, B. Karoubi, and G. Gimenez. Concept de phase spatiale : intérêt pour l'analyse de l'image. In AGI'94 Colloque Automatique, Génie informatique, Image, Poitiers, France, pages 353-356, 1994.



55. [ZHU-93b] Y.M. Zhu, Y. Gao, and R. Goutte. Texture feature discrimination based on detecting phase differences. In IEEE International Conference on Signal Processing, Beijing, P.R. China, pages 818-821, 1993.



56. [ZHU-92e] Y.M. Zhu, Y. Gao, M. Amiel, and R. Goutte. Analysis of chest CT images using Wigner distribution, October. In Conf Proc IEEE Eng Med Biol Soc, Paris, France, pages 1926-1927, 1992.



57. [ZHU-92f] Y.M. Zhu, Y. Gao, and R. Goutte. An investigation of the Wigner model for texture discrimination. In IEEE-SP Int. Symp. on time-frequency and time-scale analysis, Victoria, British Columbia, Canada, pages 539-542, 1992.



58. [ZHU-92d] Y.M. Zhu, Y. Gao, and R. Goutte. Texture features extraction using bilinear space/spatial-frequency representations. In 3rd Int. Conf. on Visual Research, Nottingham, UK, pages 1-6, 1992.



59. [ZHU-92c] Y.M. Zhu, Y. Gao, R. Goutte, and M. Amiel. Textural boundary detection using local spatial frequency analysis. In 11th IAPR Int. Conf. on Pattern Recognition, The Hague, The Netherlands, pages 53-56, 1992.



60. [ZHU-92b] Y.M. Zhu, R. Goutte, and M. Amiel. Texture segmentation using 2-D Wigner analysis : An evaluation and comparison. In J. et al. Vandewalle, editor, EUSIPCO-92, Signal Processing VI : Theory and Applications, Brussels, Belgium, pages 583-586, 1992.



61. [BASK-91c] A. Baskurt, F. Peyrin, Y.M. Zhu, and R. Goutte. Analyse d'images par utilisation de spectres locaux. In GRETSI, Juan-les-Pins, France, pages 1061-1064, 1991.



62. [BASK-91b] A. Baskurt, F. Peyrin, Y.M. Zhu, and R. Goutte. Local spectrum analysis of medical images. In SPIE Int. Conf. on Medical Imaging V : Image processing, volume 1445, San Jose, USA, pages 485-495, 1991.



63. [HANS-91] D. Hans, C. Berger-Vachon, F. Peyrin, Y.M. Zhu, and I. Kauffmann. Application de la transformation de Wigner Ville pour la caractérisation des insuffisances vélaires. In Colloque Traitement et représentation du signal et de la parole, Le Mans, France, pages 1-4, 3-4 juin 1991.



64. [PEYR-91c] F. Peyrin and Y.M. Zhu. Représentation de Wigner Ville des images : application à l'analyse de textures. In Réunion du Groupe de travail Signaux non stationnaires, GdR 134 CNRS, Paris, France, 1991.



65. [ZHU-91c] Y.M. Zhu, Y. Gao, and R. Goutte. Stereo image compression by the combined use of the DCT and binocular fusion and rivalry. In 1st Int. Symposium on 3-D images, Paris, France, pages 204-211, 26-28 septembre 1991.



66. [ZHU-91d] Y.M. Zhu, R. Goutte, and M. Amiel. On the use of the Wigner distribution for 2-D spectral analysis of images. In IEEE Workshop on multi-dimensional signal processing, Some City, Some Country, pages 2-7, 1991.



67. [ZHU-91b] Y.M. Zhu, F. Peyrin, R. Goutte, and M. Amiel. Caractérisation de textures par l'analyse spectrale locale. In 13ème colloque GRETSI, Juan-les-Pins, France, pages 989-992, 1991.

1. [ZHU-99b] Y.M. Zhu. Data fusion and image segmentation. Institut of Image. In Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, P.R. China, 1999.



2. [ZHU-99e] Y.M. Zhu. Data fusion in medical imaging. In Electrical Department, Yuannan University, Yuannan, P.R. China, 1999.



3. [ZHU-99c] Y.M. Zhu. Data fusion in medical imaging. In Biomedical Department, Zhejian University, Hanzhou, P.R. China, 1999.



4. [ZHU-99d] Y.M. Zhu. Medical image processing. In Service of Radiology, NingBo Hospital of Children and Women, NingBo, P.R. China, 1999.

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