English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Wavelet statistics of functional MRI data and the general linear model

Müller, K., Lohmann, G., Zysset, S., & von Cramon, D. Y. (2003). Wavelet statistics of functional MRI data and the general linear model. Journal of Magnetic Resonance Imaging, 17(1), 20-30. doi:10.1002/jmri.10219.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0010-E9ED-B Version Permalink: http://hdl.handle.net/11858/00-001M-0000-002C-6998-6
Genre: Journal Article

Files

show Files
hide Files
:
mueller_wavelet.pdf (Any fulltext), 2MB
Name:
mueller_wavelet.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Müller, Karsten1, Author              
Lohmann, Gabriele1, Author              
Zysset, Stefan1, Author              
von Cramon, D. Yves1, Author              
Affiliations:
1MPI of Cognitive Neuroscience (Leipzig, -2003), The Prior Institutes, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634574              

Content

show
hide
Free keywords: -
 Abstract: PURPOSE: To improve the signal-to-noise ratio (SNR) of functional magnetic resonance imaging (fMRI) data, an approach is developed that combines wavelet-based methods with the general linear model. MATERIALS AND METHODS: Ruttimann et al. (1) developed a wavelet-based statistical procedure to test wavelet-space partitions for significant wavelet coefficients. Their method is applicable for the detection of differences between images acquired under two experimental conditions using long blocks of stimulation. However, many neuropsychological questions require more complicated event-related paradigms and more experimental conditions. Therefore, in order to apply wavelet-based methods to a wide range of experiments, we present a new approach that is based on the general linear model and wavelet thresholding. RESULTS: In contrast to a monoresolution filter, the application of the wavelet method increased the SNR and showed a set of clearly dissociable activations. Furthermore, no relevant decrease of the local maxima was observed. CONCLUSION: Wavelet-based methods can increase the SNR without diminishing the signal amplitude, while preserving the spatial resolution of the image. The anatomical localization is strongly improved.

Details

show
hide
Language(s): eng - English
 Dates: 2003
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: eDoc: 239425
Other: P6880
DOI: 10.1002/jmri.10219
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Magnetic Resonance Imaging
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Chicago, IL : Society for Magnetic Resonance Imaging
Pages: - Volume / Issue: 17 (1) Sequence Number: - Start / End Page: 20 - 30 Identifier: ISSN: 1053-1807
CoNE: https://pure.mpg.de/cone/journals/resource/954925594512