Adaptive smoothing of multi-shell diffusion-weighted magnetic resonance data by msPOAS
Authors
- Becker, Saskia
- Tabelow, Karsten
ORCID: 0000-0003-1274-9951 - Mohammadi, Siawoosh
- Weiskopf, Nikolaus
- Polzehl, Jörg
ORCID: 0000-0001-7471-2658
2010 Mathematics Subject Classification
- 62P10 62G05
Keywords
- Diffusion weighted magnetic resonance imaging, POAS, Structural adaptive smoothing, Parameter choice, Multi-shell
DOI
Abstract
In this article we present a noise reduction method (msPOAS) for multi-shell diffusion-weighted magnetic resonance data. To our knowledge, this is the first smoothing method which allows simultaneous smoothing of all q-shells. It is applied directly to the diffusion weighted data and consequently allows subsequent analysis by any model. Due to its adaptivity, the procedure avoids blurring of the inherent structures and preserves discontinuities. MsPOAS extends the recently developed position-orientation adaptive smoothing (POAS) procedure to multi-shell experiments. At the same time it considerably simplifies and accelerates the calculations. The behavior of the algorithm msPOAS is evaluated on diffusion-weighted data measured on a single shell and on multiple shells.
Appeared in
- NeuroImage, 95 (2014) pp. 90--105.
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