Ronnie Wirestam
Professor
Denoising of arterial spin labeling data: wavelet-domain filtering compared with Gaussian smoothing.
Författare
Summary, in English
PURPOSE: To investigate a wavelet-based filtering scheme for denoising of arterial spin labeling (ASL) data, potentially enabling reduction of the required number of averages and the acquisition time. METHODS: ASL magnetic resonance imaging (MRI) provides quantitative perfusion maps by using arterial water as an endogenous tracer. The signal difference between a labeled image, where inflowing arterial spins are inverted, and a control image is proportional to blood perfusion. ASL perfusion maps suffer from low SNR, and the experiment must be repeated a number of times (typically more than 40) to achieve adequate image quality. In this study, systematic errors introduced by the proposed wavelet-domain filtering approach were investigated in simulated and experimental image datasets and compared with conventional Gaussian smoothing. RESULTS: Application of the proposed method enabled a reduction of the number of averages and the acquisition time by at least 50% with retained standard deviation, but with effects on absolute CBF values close to borders and edges. CONCLUSIONS: When the ASL perfusion maps showed moderate-to-high SNRs, wavelet-domain filtering was superior to Gaussian smoothing in the vicinity of borders between gray and white matter, while Gaussian smoothing was a better choice for larger homogeneous areas, irrespective of SNR.
Avdelning/ar
- MultiPark: Multidisciplinary research focused on Parkinson´s disease
- eSSENCE: The e-Science Collaboration
- Medicinsk strålningsfysik, Lund
- MR Physics
- Diagnostisk radiologi, Lund
Publiceringsår
2010
Språk
Engelska
Sidor
125-137
Publikation/Tidskrift/Serie
Magma
Volym
23
Issue
3
Fulltext
Länkar
Dokumenttyp
Artikel i tidskrift
Förlag
Springer
Ämne
- Radiology, Nuclear Medicine and Medical Imaging
Aktiv
Published
Projekt
- MRI brain perfusion quantification at 3 tesla using arterial spin labeling
Forskningsgrupp
- MR Physics
ISBN/ISSN/Övrigt
- ISSN: 1352-8661