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Journal Article

  1. [Luo-17]“Fast single image super-resolution using estimated low-frequency k-space data in MRI.”, Magn Reson Imaging, vol. 40, pp. 1-11, 2017.
  2. [ROUX-17]“Wideband 2D array design optimization with fabrication constraints for 3D US imaging”, IEEE Transactions on Ultrasonics Ferroelectrics an Frequency Control, vol. 64, 2017.
    http://ieeexplore.ieee.org/document/7581110/
  3. [ROUX-16]“2D Ultrasound Sparse Arrays Multi-Depth Radiation Optimization Using Simulated Annealing and Spiral-Array Inspired Energy Functions”, IEEE Transactions on Ultrasonics Ferroelectrics an Frequency Control, vol. 63, 2016.
    http://ieeexplore.ieee.org/document/7549037/
  4. [LI-15]H. Li, Robini, M., Magnin, I. E., and Zhu, Y. M., “Cardiac fiber unfolding by semidefinite programming”, IEEE Trans. on Biomedical Engineering, vol. 62, 2015.
  5. [Robi-15]M. Robini and Zhu, Y. M., “Generic Half-Quadratic Optimization for Image Reconstruction”, SIAM J. Imaging Sci., vol. 8, pp. 1752-1797, 2015.
  6. [FRIN-14]C. Frindel, Robini, M., and Rousseau, D., “A 3-D spatio-temporal deconvolution approach for MR perfusion in the brain”, Medical Image Analysis, vol. 18, pp. 144-160, 2014.
  7. [YANG-14]F. Yang, Zhu, Y. M., Luo, J. H., Robini, M., Liu, J., and Croisille, P., “A comparative study of different level interpolations for improving spatial resolution in diffusion tensor imaging”, IEEE Journal on Biomedical and Health Informatics, vol. 18, pp. 1317-1327, 2014.
  8. [ROBI-13]M. Robini and Reissman, P. - J., “From simulated annealing to stochastic continuation: a new trend in combinatorial optimization”, Journal of Global Optimization, vol. 56, pp. 185-215, 2013.
  9. [BAO-13]L. Bao, Robini, M., Liu, W. Y., and Zhu, Y. M., “Structure-adaptive sparse denoising for diffusion-tensor MRI”, Medical Image Analysis, vol. 17, pp. 442-457, 2013.
  10. [ROBI-13b]M. Robini, Zhu, Y. M., and Luo, J. H., “Edge-preserving reconstruction with contour-line smoothing and non-quadratic data-fidelity”, Inverse Problems and Imaging, vol. 7, pp. 1331-1366, 2013.
  11. [DIAR-13a]B. Diarra, Robini, M., Tortoli, P., Cachard, C., and Liebgott, H., “Design of optimal 2-D non-grid sparse arrays for medical ultrasound”, IEEE Transactions on Biomedical Engineering, vol. 60, pp. 3093 - 3102 , 2013.
  12. [YANG-11]F. Yang, Zhu, Y. M., Rappachi, S., Luo, J. H., Robini, M., and Croisille, P., “Interpolation of vector fields from human cardiac DT-MRI”, Physics in Medicine and Biology, vol. 56, pp. 1415-1430, 2011.
  13. [ROBI-11]M. Robini and Reissman, P. - J., “On simulated annealing with temperature-dependent energy and temperature-dependent communication”, Statistics and Probability Letters, vol. 81, pp. 915-920, 2011.
  14. [FRIN-10]C. Frindel, Robini, M., Croisille, P., and Zhu, Y. M., “A graph-based approach for automatic cardiac tractography”, Magn Reson Med, vol. 64, pp. 1215-1229, 2010.
  15. [ROBI-10]M. Robini and Magnin, I. E., “Optimization by stochastic continuation”, SIAM Journal on Imaging Sciences, vol. 3, pp. 1096-1121, 2010.
  16. [BAO-09]L. J. Bao, Zhu, Y. M., Liu, W. Y., Croisille, P., Pu, Z. B., Robini, M., and Magnin, I. E., “Denoising of human cardiac diffusion tensor magnetic resonance images using sparse representation combined with segmentation”, Phys Med Biol, vol. 54, pp. 1435–1456, 2009.
  17. [FRIN-09]C. Frindel, Robini, M., Croisille, P., and Zhu, Y. M., “Comparison of regularization methods for human cardiac diffusion tensor MRI”, Med Image Anal, vol. 13, pp. 405–418, 2009.
  18. [NJIWA-07]J. Y. Njiwa, Zhu, Y. M., Robini, M., and Magnin, I. E., “Magnetic Resonance Image Reconstruction Using Analytic Image Representation”, Nuclear Instruments and Methods in Physics Research A, vol. 571, pp. 73-76, 2007.
  19. [ROBI-07]M. Robini and Magnin, I. E., “Radiographic Testing of Anomalies in Thick Metal Components: Fitting the Standard Line-Integral Model”, IEEE Trans Nucl Sci, vol. 54, pp. 1285-1297, 2007.
  20. [ROBI-07b]M. Robini, Lachal, A., and Magnin, I. E., “A Stochastic Continuation Approach to Piecewise Constant Reconstruction”, IEEE Trans Image Proces, vol. 16, pp. 2576-2589, 2007.
  21. [ROBI-03]M. Robini and Magnin, I. E., “Stochastic nonlinear image restoration using the wavelet transform”, IEEE Trans Image Proces, vol. 12, pp. 890-905, 2003.
  22. [ROBI-02]M. Robini, Bresler, Y., and Magnin, I. E., “On the convergence of Metropolis-type and annealing with constraints”, Probab Eng Inform Sc, vol. 4, pp. 427-452, 2002.
  23. [BOUK-02]D. Boukerroui, Noble, A., Robini, M., and Brady, J. M., “Enhancement of contrast regions in sub-optimal ultrasound images with application to echocardiography”, Ultrasound Med Biol, vol. 27, pp. 1583–1594, 2002.
  24. [ROBI-99b]M. Robini, Rastello, T., and Magnin, I. E., “Simulated annealing, acceleration techniques and image restoration”, IEEE Trans Image Proces, vol. 8, pp. 1374–1387, 1999.
  25. [ROBI-97a]M. Robini, Magnin, I. E., Benoit-Cattin, H., and Baskurt, A., “Two dimensional ultrasonic flaw detection based on the wavelet packet transform”, IEEE Trans Ultrason Ferroelectr Freq Control, vol. 44, pp. 1382-1394, 1997.
  26. [DITT-95]A. Dittmar, Rada, H., Delhomme, G., Verney-Maury, E., Collet, C., Roure, R., Unterreiner, R., Robini, M., and Delemer, C., “A multi-sensor system for the non-invasivemeasurement of the activity of autonomic nervous system”, Sens Actuators B, vol. 27, pp. 461-464, 1995.

Conference Paper

  1. [ROBI-13c]M. Robini, Freud, N., and Létang, J. M., “Efficient simulated annealing for full inverse treatment planning”, in IEEE Medical Imaging Conference, Seoul (South Korea), In Press.
  2. [ROUX-17c]“Validation of optimal 2D sparse arrays in focused mode phantom experiments”, in IEEE International Ultrasonics Symposium, Washington, USA, 2017.
  3. [DIAR-16]“Comparison of different optimized irregular sparse 2D ultrasound arrays ”, in IEEE International Ultrasonics Symposium, Tours, France., 2016, pp. 1-4.
    http://ieeexplore.ieee.org/document/7728414/
  4. [ROUX-15c]E. Roux, Robini, M., Ramalli, A., Tortoli, P., C., C., and Liebgott, H., “Modélisation et simulation acoustique pour l’optimisation de sondes échographiques 2D par recuit simulé”, in GRETSI, 2015, p. accepted.
    https://hal.archives-ouvertes.fr/hal-01286079/
  5. [ROUX-15a]E. Roux, Ramalli, A., Tortoli, P., Cachard, C., Robini, M., and Liebgott, H., “Speed-Up of Acoustic Simulation Techniques for 2D Sparse Array Optimization by Simulated Annealing”, in IEEE International Ultrasonics Symposium, 2015, pp. 1–4.
    http://ieeexplore.ieee.org/document/7329330/
  6. [ROUX-15b]E. Roux, Ramalli, A., Robini, M., Liebgott, H., C., C., and Tortoli, P., “Spiral Array Inspired Multi-Depth Cost Function for 2D Sparse Array Optimization”, in IEEE International Ultrasonics Symposium, 2015, pp. 1-4.
    http://ieeexplore.ieee.org/document/7329187/
  7. [Ozon-14]M. Ozon, Robini, M., and Zhu, Y. M., “Global DT-MRI Tractography Using Elastic Graphs”, in IEEE EMBC, Chicago, USA, 2014, pp. 26-30.
  8. [Li-14]H. Y. Li, Robini, M., and Zhu, Y. M., “Unfolding Cardiac Fibers by Dimensionality Reduction”, in IEEE EMBC, Chicago, USA, 2014, pp. 26-30.
  9. [ROUX-14]E. Roux, Diarra, B., Robini, M., Cachard, C., Tortoli, P., and Liebgott, H., “Realistic acoustic simulation of 2D probe elements in simulated annealing sparse array optimization”, in IEEE International Ultrasonics Symposium, Chicago, Illinois, USA, 2014, pp. 2125–2128.
    http://ieeexplore.ieee.org/document/6931817/
  10. [DIAR-14]B. Diarra, Robini, M., Roux, E., Tortoli, P., Liebgott, H., and Cachard, C., “Optimization of free-moving elements in 2D ultrasound sparse arrays”, in IEEE International Ultrasonics Symposium, Chicago, Illinois, USA, 2014, pp. 2189–2192.
    http://ieeexplore.ieee.org/document/6931734/
  11. [Robi-14]M. Robini and Zhu, Y. M., “Nonconvex half-quadratic image reconstruction with wavelet-domain sparsity constraints”, in International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV), Las Vegas, USA, 2014, p. 1p.
  12. [OZON-13]M. Ozon, Robini, M., Croisille, P., Frindel, C., and Zhu, Y. M., “Toward temporal fiber”, in Computing in Cardiology, Zaragoza (Spain), 2013, pp. 567-570.
  13. [FRIN-13b]C. Frindel, Rousseau, D., and Robini, M., “Approche 3D spatio-temporelle pour la déconvolution en imagerie de perfusion du cerveau”, in GRETSI '13 : 24ème colloque GRETSI sur le Traitement du Signal et des Images, Brest, France, 2013.
  14. [DIAR-13b]B. Diarra, Robini, M., Liebgott, H., Cachard, C., and Tortoli, P., “Variable-size elements in 2D sparse arrays for 3D medical ultrasound”, in IEEE International Ultrasonics Symposium, Prague, Czech Republic, 2013.
  15. [LI-12]H. Y. Li, Robini, M., Yang, F., and Zhu, Y. M., “A neighborhood-based probabilistic approach for fiber tracking in human cardiac DTI”, in IEEE Int. Symp. Biomedical Imaging, Barcelona (Spain), 2012, pp. 9-13.
  16. [ROBI-12f]M. Robini, “Graph drawing by stochastic continuation”, in Int. Conf. Computer Graphics and Virtual Reality, Las Vegas (Nevada), 2012, pp. 33-39.
  17. [ROBI-12d]M. Robini, “A generalized simulated annealing approach to image reconstruction”, in 6th SIAM conf. on Imaging Science, Philadelphia (Pennsylvania), 2012, p. 115.
  18. [DIAR-12b]B. Diarra, Liebgott, H., Robini, M., Tortoli, P., and Cachard, C., “Optimized 2-D array design for ultrasound imaging”, in EUSIPCO, Bucharest, Romania, 2012, pp. 2718-2722.
  19. [YANG-12]F. Yang, Zhu, Y. M., Robini, M., and Croisille, P., “DT-MRI interpolation: at what level?”, in IEEE Int. Conf. Signal Processing, Beijing (China), 2012, pp. 737-740.
  20. [ROBI-12c]M. Robini and Viverge, P. - J., “Image reconstruction with multiresolution edge-continuation and non-quadratic data fidelity”, in 6th SIAM conf. on Imaging Science, Philadelphia (Pennsylvania), 2012, p. 115.
  21. [ROBI-12]M. Robini, Zhu, Y. M., and Luo, J. H., “A generic half-quadratic algorithm for signal reconstruction”, in 9th IMA Int. Conf. Mathematics in Signal Processing, Birmingham (UK), 2012, pp. 1-4.
  22. [ROBI-11c]M. Robini, Viverge, P. - J., Zhu, Y. M., and Luo, J. H., “Globally convergent edge-preserving reconstruction with contour-line smoothing”, in 7th Int. Conf. Pattern Recognition and Computer Vision, Amsterdam (Netherlands), 2011, pp. 885-890.
  23. [ROBI-11b]M. Robini, Smekens, F., and Sixou, B., “Optimal inverse treatment planning by stochastic continuation”, in IEEE Int. Symp. Biomedical Imaging (ISBI-11), Chicago (Illinois), 2011, pp. 1792-1796.
  24. [ROBI-10b]M. Robini and Labruyère, J. - P., “Efficient implicit smoothing of contour lines for image reconstruction”, in 5th SIAM conf. on Imaging Science, Chicago (Illinois), 2010, p. 100.
  25. [YANG-09]F. Yang, Zhu, Y. M., Song, X., Rappachi, S., Croisille, P., and Robini, M., “Interpolation avec réduction du bruit du champ de vecteurs 3D en IRM cardiaque du tenseur de diffusion”, in GRETSI, Dijon, France, 2009.
  26. [STEP-09]E. Stephant, Frindel, C., Robini, M., Fanton, L., Viallon, M., and Croisille, P., “Analytic description of MR diffusion indices in ex-vivo human hypertrophic cardiomyopathy”, in ISMRM, Honolulu, USA, 2009.
  27. [FRIN-09]C. Frindel, Robini, M., Schaerer, J., Croisille, P., and Zhu, Y. M., “Improved global cardiac tractography with simulated annealing”, in IEEE ICIP, Cairo, Egypt, 2009, pp. 813-816.
  28. [FRIN-09b]C. Frindel, Robini, M., Croisille, P., and Zhu, Y. M., “Cardiac Fibre Trace Clustering for the interpretation of the Human Heart Architecture”, in Proc. 4th Int. Conf. FIMH, Nice, France, 2009, pp. 39-48.
  29. [ROBI-09]M. Robini, Viverge, P. - J., Zhu, Y. M., and Magnin, I. E., “Edge-preserving image reconstruction with wavelet-domain edge continuation”, in Proc. 6th Int. Conf. Image Analysis and Recognition, Halifax, Canada, 2009, pp. 13-22.
  30. [FRIN-09]C. Frindel, Rapacchi, S., Robini, M., Wen, H., Viallon, M., Fanton, L., and Croisille, P., “In vivo cardiac NMR Diffusion Weighted Imaging(DWI) for the human heart: improved quantification of FA and MD by edge-preserving regularization”, in ISMRM, Honolulu, USA, 2009.
  31. [FRIN-08]C. Frindel, Gueth, P., Clarysse, P., Zhu, Y. M., and Robini, M., “A global approach to cardiac tractography”, in Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on, 2008, pp. 883–886.
  32. [ROBI-08]M. Robini and Magnin, I. E., “Stochastic continuation”, in 4th SIAM conf. on Imaging Science, San Diego (California), 2008, p. 134.
  33. [FRIN-07]C. Frindel, Robini, M., Rapacchi, S., Stephant, E., Zhu, Y. M., and Croisille, P., “Towards in vivo diffusion tensor MRI on human heart using edge-preserving regularization”, in Proc. 29th Int. Conf. IEEE EMBS, Lyon, France, 2007, pp. 6007-6010.
  34. [BAO-07]L. Bao, Zhu, Y. M., Liu, W. Y., Robini, M., Pu, Z., and Magnin, I. E., “Analysis of cardiac diffusion tensor magnetic resonance images using sparse representation”, in Proc. 29th Int. Conf. IEEE EMBS, Lyon, France, 2007, pp. 4516-4519.
  35. [ROBI-07a]M. Robini and Magnin, I. E., “Stochastic Continuation. Opening new horizons to solving difficult optimization problems”, in Proc. 14th IEEE Workshop on Statistical Signal Processing, Madison, Wisconsin, 2007, pp. 264-268.
  36. [ROBI-06c]M. Robini, Labruyere, J. P., and Magnin, I. E., “Radiographic inspection of thick metal components, Part II: a new stochastic approach to 3-D reconstruction”, in IEEE Nuclear Science Symposium, San Diego, CA, 2006, vol. 2, pp. 973-977.
  37. [ROBI-06b]M. Robini, Labruyere, J. P., and Magnin, I. E., “Radiographic inspection of thick metal components, Part I: fitting the standard linear image formation model”, in IEEE Nuclear Science Symposium, San Diego, CA, 2006, vol. 2, pp. 964-968.
  38. [ROBI-06]M. Robini and Magnin, I. E., “Piecewise constant reconstruction using a stochastic continuation approach”, in IEEE Int. Symp. Signal Processing and Information Technology, Vancouver, Canada, 2006, pp. 874-878.
  39. [YANK-06a]J. Yankam Njiwa, Zhu, Y. M., Robini, M., and Magnin, I. E., “Magnetic resonance image reconstruction using the notion of analytic image”, in EUROMEDIM Conference(Euromedim 2006), Marseille, France, 2006, pp. 73-76.
  40. [YANK-06]J. Yankam Njiwa, Zhu, Y. M., Robini, M., Luo, J. H., and Magnin, I. E., “Image reconstruction from partial k-space using the notion of analytic image”, in Int. Conf. Signal Processing, Guilin, R.P. China, 2006, pp. 994-997.
  41. [NEYR-05]B. Neyran, Carme, S., Wiart, M., Robini, M., and Canet-Soulas, E., “Mapping myocardial perfusion with an intravascular MR contrast agent, a robust estimation by a spatially constrained approach”, in Computers in Cardiology, Lyon, France, 2005, pp. 407-410.
  42. [JARR-03]A. Jarrot, Liebgott, H., Delachartre, P., and Robini, M., “Edge-Preserving reconstruction for Young's modulus recovery from ultrasonic data”, in IEEE Ultrasonics Symposium, Honolulu, Hawaii, USA, 2003, pp. 1919-1922.
  43. [ROBI-99]M. Robini and Magnin, I. E., “3-D reconstruction from a few radiographs using the Metropolis dynamics with annealing”, in IEEE International Conference on Image Processing ICIP'99, Kobe, Japan, 1999, vol. III, pp. 876-880.
  44. [ROBI-98]M. Robini and Magnin, I. E., “Simulated annealing based shift-variant image restoration using the multiresolution wavelet transform”, in IEEE Int. Conf. Image Processing, Chicago, Illinois, USA, 1998, vol. 1, pp. 560–564.
  45. [GORC-97d]J. M. Gorce, Friboulet, D., Robini, M., Bijnens, B., and Magnin, I. E., “Analysis of RF signals in echographic images using a regularized autoregressive model”, in Proceedings 11th Int Conf on Computer Assisted Radiology, Berlin, Germany, 1997, p. 981.
  46. [GORC-97b]J. M. Gorce, Friboulet, D., Robini, M., Bijnens, B., and Magnin, I. E., “Regularized autoregressive model preserving spatial discontinuities for analysis of radio-frequency signals in echographic images”, in 6e Colloque GRETSI, Grenoble, France, 1997, pp. 1363–1366.
  47. [ROBI-97b]M. Robini, Rastello, T., Vray, D., and Magnin, I. E., “Space-variant deconvolution for synthetic aperture imaging using simulated annealing”, in IEEE Int Conf Image Processing, Santa Barbara, California, USA, 1997, vol. 1, pp. 432–435.
  48. [ROBI-95b]M. Robini, Magnin, I. E., Benoit-Cattin, H., and Baskurt, A., “Application of the wavelet packet transform to flaw detection in ultrasound B-scans”, in IEEE Ultrasonics Symposium, Seattle, Washington, USA, 1995, vol. 1, pp. 747–750.
  49. [ROBI-95a]M. Robini, Magnin, I. E., and Lavayssière, B., “Wavelet packets based flaw detection in Ultrasonic B-scan images”, in International Conference on Quality Control by Artificial Vision, Le Creusot, France, 1995, pp. 37–47.

Book Chapter

  1. [ROBI-12b]M. Robini, “Theoretically grounded acceleration techniques for simulated annealing”, in Handbook of Optimization, From Classical to Modern Approach, I. Zelinka, Snasel, V., and Abraham, A. Springer, 2012, pp. 311-336.

Thesis

  1. [ROBI-98b]M. Robini, “Inversion bayesienne et algorithmes stochastiques de types recuit. Application à la restauration d'images et à la recontruction 3-D à partir d'un nombre très limité de projections”, INSA Lyon, 1998.
    Barlaud M. (rap.), Chassery J.M., Geman D. (rap.), Jousselin A., Magnin I.E. (dir.), Preteux F. (rap.) et Prost R.

Miscellaneous

  1. [ROUX-15d]E. Roux, Ramalli, A., Tortoli, P., Robini, M., Liebgott, H., and Cachard, C., “Optimisation du rayonnement acoustique de sondes parcimonieuses pour l’échographie 3D temps-réel”. p. accepted, 2015.