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9 résultats
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Méthode d'approximation variationnelle pour l'analyse de données d'IRM fonctionnelle acquise par Arterial Spin LabellingGRETSI, Sep 2015, Lyon, France
Communication dans un congrès
hal-01254176v1
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Physiological models comparison for the analysis of ASL FMRI data12th IEEE International Symposium on Biomedical Imaging, ISBI 2015, Apr 2015, New York, United States. pp.1348-1351, ⟨10.1109/ISBI.2015.7164125⟩
Communication dans un congrès
hal-01249014v1
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Comparison of Stochastic and Variational Solutions to ASL fMRI Data AnalysisMedical Image Computing and Computer-Assisted Intervention - MICCAI 2015, Oct 2015, Munich, Germany. pp.85-92, ⟨10.1007/978-3-319-24553-9_11⟩
Communication dans un congrès
hal-01249018v1
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Variational Physiologically Informed Solution to Hemodynamic and Perfusion Response Estimation from ASL fMRI Data2015 International Workshop on Pattern Recognition in NeuroImaging, Jun 2015, Stanford, CA, United States. pp.57-60, ⟨10.1109/PRNI.2015.12⟩
Communication dans un congrès
hal-01249015v1
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Hemodynamically informed parcellation of cerebral FMRI dataICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing, May 2014, Florence, Italy. pp.2079-2083, ⟨10.1109/ICASSP.2014.6853965⟩
Communication dans un congrès
hal-01100186v2
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Physiologically Informed Bayesian Analysis of ASL fMRI DataBAMBI 2014 - First International Workshop on Bayesian and grAphical Models for Biomedical Imaging, Sep 2014, Boston, United States. pp.37 - 48, ⟨10.1007/978-3-319-12289-2_4⟩
Communication dans un congrès
hal-01100266v1
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Physiologically informed Bayesian analysis of ASL fMRI dataStatistical Challenges in Neuroscience workshop, Sep 2014, Warwick, United Kingdom
Communication dans un congrès
hal-01107613v1
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PyHRF: A Python Library for the Analysis of fMRI Data Based on Local Estimation of the Hemodynamic Response Function16th Python in Science Conference (SciPy 2017), Jul 2017, Austin, TX, United States. pp.34-40, ⟨10.25080/shinma-7f4c6e7-006⟩
Communication dans un congrès
hal-01566457v1
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Statistical Models for the analysis of ASL and BOLD Magnetic Resonance modalities to study brain function and diseaseMedical Imaging. Université Grenoble Alpes, 2016. English. ⟨NNT : 2016GREAM086⟩
Thèse
tel-01440495v2
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