Functional and dynamic magnetic resonance imaging using vector adaptive weights smoothing

Jörg Polzehl, Vladimir G. Spokoiny

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

We consider the problem of statistical inference for functional and dynamic magnetic resonance imaging (MRI). A new approach is proposed which extends the adaptive weights smoothing procedure of Polzehl and Spokoiny that was originally designed for image denoising. We demonstrate how the adaptive weights smoothing method can be applied to time series of images, which typically occur in functional and dynamic MRI. It is shown how signal detection in functional MRI and the analysis of dynamic MRI can benefit from spatially adaptive smoothing. The performance of the procedure is illustrated by using real and simulated data.

Original languageEnglish
Pages (from-to)485-501
Number of pages17
JournalJournal of the Royal Statistical Society. Series C: Applied Statistics
Volume50
Issue number4
DOIs
Publication statusPublished - 2001
Externally publishedYes

Keywords

  • Adaptive weights smoothing
  • Functional and dynamic magnetic resonance imaging
  • Signal detection
  • Spatial adaptation

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