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Abstract #3037

Robust Perfusion Maps in Arterial Spin Labeling by Means of M-Estimators

Camille Maumet1, Pierre Maurel1, Jean-Christophe Ferr1, 2, Christian Barillot1

1Inria, IRISA, RENNES, Brittany, France; 2Department of Neuroradiology, CHU Rennes, Rennes, Brittany, France

In Arterial Spin Labeling (ASL), the perfusion signal is usually extracted by averaging the volumes acquired over several repetitions. Unfortunately, the presence of artefacts is a well-known source of outliers and can drastically alter the perfusion map obtained by averaging. In this paper, we propose to compute ASL perfusion maps using Huber's M-estimator, a robust statistical function that is not overly impacted by outliers. This method is compared to an empirical approach, previously introduced in the literature, based on z-score thresholding. Overall, Huber's M-estimator is more robust than z-thresholding. Both robust approaches outperform the sample mean in the presence of outliers.