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Abstract #5070

Improved Denoising of Dynamic Arterial Spin Labeling with Infimal Convolution of Total Generalized Variation Functionals (ICTGV)

Matthias Schloegl1, Stefan Spann1, Christoph Aigner1, Martin Holler2, Kristian Bredies2, and Rudolf Stollberger1

1Institute of Medical Engineering, Graz University of Technology, Graz, Austria, 2Institute of Mathematics and Scientific Computing, University of Graz, Austria

Dynamic arterial spin labeling MRI provides important quantitative information about blood arrival time and perfusion. However, the inherently low signal-to-noise ratio requires repeated measurements to achieve a reasonable image quality. This leads to long acquisition times and hence increases the risk of motion artifacts, which impedes clinical applicability. To overcome this limitation we propose to reconstruct the dynamic ASL data employing ICTGV regularization from a reduced number of averages. The performance of the method is evaluated on synthetic and in-vivo ASL data.

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