Export 81 results:

Journal Article

  1. [LART-10]C. Lartizien, Aubin, J. - B., and Buvat, I., Comparison of Bootstrap Resampling Methods for 3-D PET Imaging, IEEE Transactions on Medical Imaging, vol. 29, pp. 1442-1454, 2010.

Conference Paper

  1. [AZAM-16a]Converting SVDD scores into probability estimates, in European Symposium on Articial Neural Networks, Computational Intelligence and Machine Learning (ESANN), 2016.
  2. [AZAM-15]M. El Azami, Bouet, R., Jung, J., Hammers, A., and Lartizien, C., Combining multi-parametric MR images for the detection of epileptogenic lesions, in 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), New York, USA, 2015, pp. p 122-125.
  3. [AZAM-14]M. El Azami, Lartizien, C., and Canu, S., Robust outlier detection with L0-SVDD, in European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN), Bruges (Belgium), 2014.
  4. [HILA-13b]E. Hilaire, Robert, C., Lojacono, X., Lartizien, C., Buvat, I., and Maxim, V., Imagerie Compton en protonthérapie : de la simulation GATE à la reconstruction d’images, in XXIVème Colloque GRETSI - Traitement du Signal et des Images (GRETSI'13), Brest, France, 2013, p. 1--4.
  5. [AZAM-13]M. El Azami, Hammers, A., Costes, N., and Lartizien, C., Computer Aided Diagnosis of Intractable Epilepsy with MRI Imaging Based on Textural Information, in 2013 International Workshop on Pattern Recognition in Neuroimaging (PRNI), Philadelphia, USA, 2013, pp. 90-93.
  6. [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 .
  7. [NIAF-11b]E. Niaf, Flamary, R., Lartizien, C., and Canu, S., Handling uncertainties in SVM classification, in IEEE Workshop on Statistical Signal Processing, 2011, pp. 757-760.
  8. [MARA-11]S. Marache, Prost, R., Rouet, J. M., and Lartizien, C., Incorporating Patient-Specific Variability in the OncoPET_DB Database, in IEEE Nuclear Science Symposium and Medical Imaging Conference , 23-29 October 2011,Valencia,Spain, 2011, pp. 4184 - 4187 .
  9. [MARA-10]S. Marache, Lamare, F., Fayad, H., Visvikis, D., Prost, R., Rouet, J. M., and Lartizien, C., Impact of Respiratory Motion Correction on the Detection of Small Lesions in Whole-body PET Imaging: A Simulation Study, in IEEE Nuclear Science Symposium and Medical Imaging Conference, 30 October - 6 November 2010, Knoxville, Tennessee, USA. , 2010, pp. 3531-3533.
  10. [TABA-09]J. Tabary, Marache, S., Valette, S., Segars, W., and Lartizien, C., Realistic X-Ray CT Simulation of the XCAT Phantom with SINDBAD, in Proc. of the 2009 IEEE NSS and MIC Conference, Orlando, USA, 2009, pp. 3980 - 3983.
  11. [BABO-06]L. Baboi, Milot, L., Pilleul, F., Lartizien, C., and Beuf, O., Synchronization strategies in T2-weighted MR imaging for detection of mouse liver metastasis, in International Society of Magnetic Resonance in Medicine, 14th Scientific Meeting, Seattle, Washington, USA, 2006, p. 2217.
  12. [LART-05b]C. Lartizien and Buvat, I., Comparison of 3D PET data bootstrap resampling methods for numerical observers studies, in Proc of the 2005 IEEE NSS and MIC Conference, Puerto Rico, USA, 2005, pp. 2138-2147.


  1. [NIAF-12c]E. Niaf, Aide au diagnostic du cancer de la prostate par IRM multi-paramétrique : une approche par classification supervisée, Université Claude Bernard Lyon 1, Lyon, 2012.
    Jury : Isabelle Bloch (rapporteur), Michèle Rombaut (rapporteur), Olivier Basset, Stéphane Canu, Olivier Rouvière (superviseur), Carole Lartizien (co-superviseur)