Robust Cerebral Blood Flow Map Estimation in Arterial Spin Labeling

Abstract : Non-invasive measurement of Cerebral Blood Flow (CBF) is now feasible thanks to the introduction of Arterial Spin Labeling (ASL) Magnetic Resonance Imaging (MRI) techniques. To date, the low signal-to-noise ratio of ASL gives us no option but to repeat the acquisition in order to accumulate enough data to get a reliable signal. Perfusion signal is usually extracted by averaging across the repetitions. However, due to its zero breakdown point, the sample mean is very sensitive to outliers. A single outlier can thus have strong detrimental effects on the sample mean estimate. In this paper, we propose to estimate robust ASL CBF maps by means of M-estimators to overcome the deleterious effects of outliers. The behavior of this method is compared to z-score thresholding as recommended in [8]. validation on simulated and real data is provided. Quantitative validation is undertaken by measuring the correlation with the most widespread technique to measure perfusion with MRI: Dynamic Susceptibility weighted Contrast (DSC).
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Communication dans un congrès
International Workshop on Multimodal Brain Image Analysis (MBIA), held in conjunction with MICCAI 2012, Oct 2012, Nice, France. pp.215-224


http://www.hal.inserm.fr/inserm-00724974
Contributeur : Camille Maumet <>
Soumis le : mardi 16 octobre 2012 - 14:00:22
Dernière modification le : mercredi 27 novembre 2013 - 09:00:44

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Camille Maumet, Pierre Maurel, Jean-Christophe Ferré, Christian Barillot. Robust Cerebral Blood Flow Map Estimation in Arterial Spin Labeling. International Workshop on Multimodal Brain Image Analysis (MBIA), held in conjunction with MICCAI 2012, Oct 2012, Nice, France. pp.215-224. <inserm-00724974>

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