Fabrice Pautot

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A new deconvolution algorithm, the Bayesian estimation algorithm, was reported to improve the precision of parametric maps created using perfusion computed tomography. However, it remains unclear whether quantitative values generated by this method are more accurate than those generated using optimized deconvolution algorithms of other software packages.(More)
A delay-insensitive probabilistic method for estimating hemodynamic parameters, delays, theoretical residue functions, and concentration time curves by computed tomography (CT) and magnetic resonance (MR) perfusion weighted imaging is presented. Only a mild stationarity hypothesis is made beyond the standard perfusion model. New microvascular parameters(More)
PURPOSE We compared the performances of a Bayesian estimation method and oscillation index singular value decomposition (oSVD) deconvolution for predicting final infarction using data previously obtained from 10 cynomolgus monkeys with permanent unilateral middle cerebral artery (MCA) occlusion. METHODS We conducted baseline perfusion-weighted imaging 3(More)
Indices of collateral flow deficit derived from MR perfusion imaging that are predictive of MCA-M1 recanalization after intravenous thrombolysis have been recently reported. Our objective was to test the performance of such MRI-derived collateral flow indices for prediction of recanalization after endovascular thrombectomy. Fifty-seven patients with MCA-M1(More)
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