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Journal Article

  1. [WANG-17]“Application of a LBGK-Based 4D Image Segmentation Method to a 4D-CTA Acquisition of an Intracranial Aneurysm Phantom”, Computing in Science and Engineering, vol. 19, In Press.
  2. [FARO-18]“Ultrasound spatiotemporal despeckling via Kronecker wavelet-Fisz thresholding”, Signal, Image and Video Processing, 2018.PDF icon Farouj-18 Ultrasound spatiotemporal despeckling via Kronecker wavelet-Fisz thresholding.pdf (564.21 KB)
  3. [FARO-17]“Hyperbolic Wavelet-Fisz denoising for a model arising in ultrasound imaging”, IEEE Transactions on Computational Imaging, vol. 3, pp. 1-10, 2017.
  4. [WANG-16]“Multilevel segmentation of intracranial aneurysms in CT angiography images”, Medical Physics, vol. 43, pp. 1777 - 1786, 2016.
  5. [FRAU-14]F. Frauziols, Mollimard, J., Navarro, L., Badel, P., Viallon, M., Testa, R., and Avril, S., “Prediction of the biomechanical effects of compression therapy by finite element modeling and ultrasound elastography.”, IEEE Trans Biomed Eng., 2014.
    http://www.ncbi.nlm.nih.gov/pubmed/25494500
  6. [CHEN-14]Y. Chen, Navarro, L., Wang, Y., and Courbebaisse, G., “Segmentation of the Thrombus of Giant Intracranial Aneurysms from CT Angiography Scans with Lattice Boltzmann Method”, Medical Image Analysis Journal, Elsevier, vol. 18, pp. 1-8, 2014.
  7. [NAVA-13a]L. Navarro, Deng, G., and Courbebaisse, G., “The symmetric logarithmic image processing model”, Digital Signal Processing Journal, Elsevier, vol. 23, pp. 1337-1343, 2013.
  8. [COUR-11]G. Courbebaisse, Bouffanais, R., Navarro, L., Leriche, E., and Deville, M. O., “Time-Scale joint representation of DNS and LES numerical data”, Computers & Fluids Journal, Elsevier, vol. 43, pp. 38-45, 2011.
  9. [NAVA-11]“Symmetric Logarithmic Image Processing Model, Application to Laplacian Edge Detection”, HAL, 2011.
    https://hal.archives-ouvertes.fr/hal-00709350/
  10. [NAVA-08a]L. Navarro, Courbebaisse, G., and Pinoli, J. C., “Continuous frequency and phase spectrograms : A study of their 2D and 3D capabilities. Application to musical signal analysis”, Journal of Zhejiang University SCIENCE A, vol. 9, pp. 199-206, 2008.

Conference Paper

  1. [FARO-15]Y. Farouj, Navarro, L., Clausel, M., and Delachartre, P., “Débruitage de séquences d'images dynamiques par ondelettes espace-temps hyperboliques”, in Gretsi, 2015.
  2. [NAVA-15]L. Navarro, Courbebaisse, G., and Roux, C., “Une redéfinition des conditions aux limites de la méthode Lattice Boltzmann pour le débruitage d’images”, in GRETSI 2015, Lyon, 2015.
  3. [FARO-14b]Y. Farouj, Navarro, L., Clausel, M., and Delachartre, P., “A VARIATIONAL SHEARLET-BASED MODEL FOR AORTIC STENT DETECTION”, in In Proc. IEEE Conf. on Signal Processing (ICSP'14), HangZhou, China, 2014, pp. 1052-1056.
  4. [FARO-14a]Y. Farouj, Wang, L., Clarysse, P., Navarro, L., Clausel, M., and Delachartre, P., “Cardiac Motion Analysis using wavelet projections from Tagged MR sequences”, in IEEE International Conference on Image Processing (ICIP'14), Paris, 2014, p. Accepted.
  5. [COUR-10]G. Courbebaisse, Bouffanais, R., Navarro, L., and Deville, M. O., “Multiscale comparison of the turbulent DNS data and LES data of the lid-driven cavity flow”, in High Accuracy Flow Simulations, EPFL Lausanne, Switzerland, 2010.
  6. [COUR-10b]R. Bouffanais, Courbebaisse, G., Navarro, L., and Deville, M. O., “Wavelet Analysis of the Turbulent LES Data of the Lid-Driven Cavity Flow”, in International Conference on Turbulence and Interactions - TI 2009, Martinique, France, 2010, pp. 87-94, vol. 110.
  7. [NAVA-08b]L. Navarro, Courbebaisse, G., and Pinoli, J. C., “Reassigned Three Dimentional Phase Spectrogram and Ground Reaction Forces”, in EUSIPCO, European Signal Processing Conference, Lausanne, Switzerland, 2008, p. (CD).

Book Chapter

  1. [NAVA-14]L. Navarro, Courbebaisse, G., and Jourlin, M., “Logarithmic Wavelets”, in Advances in Imaging and Electron Physics, Academic Press., vol. 183, P. Hawkes 2014, pp. 41-98.