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Proceedings Paper

Denoising arterial spin labeling MRI using tissue partial volume
Author(s): Jan Petr; Jean-Christophe Ferre; Jean-Yves Gauvrit; Christian Barillot
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Paper Abstract

Arterial spin labeling (ASL) is a noninvasive MRI method that uses magnetically labeled blood to measure cerebral perfusion. Spatial resolution of ASL is relatively small and as a consequence perfusion from different tissue types is mixed in each pixel. An average ratio of gray matter (GM) to white matter (WM) blood flow is 3.2 to 1. Disregarding the partial volume effects (PVE) can thus cause serious errors of perfusion quantification. PVE also complicates spatial filtering of ASL images as apart from noise there is a spatial signal variation due to tissue partial volume. Recently, an algorithm for correcting PVE has been published by Asllani et al. It represents the measured magnetization as a sum of different tissue magnetizations weighted by their fractional volume in a pixel. With the knowledge of the partial volume obtained from a high-resolution MRI image, it is possible to separate the individual tissue contributions by linear regression on a neighborhood of each pixel. We propose an extension of this algorithm by minimizing the total-variation of the tissue specific magnetization. This makes the algorithm more flexible to local changes in perfusion. We show that this method can be used to denoise ASL images without mixing the WM and GM signal.

Paper Details

Date Published: 12 March 2010
PDF: 9 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76230L (12 March 2010); doi: 10.1117/12.844443
Show Author Affiliations
Jan Petr, INRA (France)
Univ. of Rennes I, CNRS, UMR 6074 (France)
INSERM (France)
Jean-Christophe Ferre, INRA (France)
Univ. Hospital of Rennes (France)
Univ. of Rennes I, CNRS, UMR 6074 (France)
Jean-Yves Gauvrit, INRA (France)
Univ. Hospital of Rennes (France)
Univ. of Rennes I, CNRS, UMR 6074 (France)
Christian Barillot, INRA (France)
Univ. of Rennes I, CNRS, UMR 6074 (France)
INSERM (France)


Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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