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Detection of resting-state brain activity in magnetic resonance images through wavelet feature cluster analysis

Geert Verdoolaege UGent, Leslie Vlerick UGent and Eric Achten UGent (2011) IEEE International Conference on Image Processing ICIP. p.2717-2720
abstract
Magnetic resonance imaging studies of the resting brain have recently revealed the existence of low-frequency fluctuations of the cerebral hemodynamics. It has been suggested that these fluctuations are linked to baseline neural activity, organized in functional networks. This paper presents a novel method for the detection of these resting-state networks from blood-oxygen level dependent signals, through their wavelet representation in the appropriate frequency range. A valley-seeking clustering principle is employed, requiring no a priori knowledge of the number of functional networks. The technique is applied to a data set acquired at rest and is shown to retrieve a number of identifiable functional networks. The method is proposed as an alternative to e. g. independent component analysis and exhibits an enhanced network separation capability and stability against noise.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
wavelet, fMRI, resting state, clustering
in
IEEE International Conference on Image Processing ICIP
issue title
2011 18th IEEE international conference on image processing (ICIP 2011)
pages
2717 - 2720
publisher
IEEE
place of publication
New York, NY, USA
conference name
18th IEEE International conference on Image Processing (ICIP 2011)
conference location
Brussels, Belgium
conference start
2011-09-11
conference end
2011-09-14
Web of Science type
Proceedings Paper
Web of Science id
000298962502198
ISBN
9781457713026
project
The integrative neuroscience of behavioral control (Neuroscience)
language
English
UGent publication?
yes
classification
P1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1934381
handle
http://hdl.handle.net/1854/LU-1934381
date created
2011-10-21 15:52:04
date last changed
2013-07-17 15:50:11
@inproceedings{1934381,
  abstract     = {Magnetic resonance imaging studies of the resting brain have recently revealed the existence of low-frequency fluctuations of the cerebral hemodynamics. It has been suggested that these fluctuations are linked to baseline neural activity, organized in functional networks. This paper presents a novel method for the detection of these resting-state networks from blood-oxygen level dependent signals, through their wavelet representation in the appropriate frequency range. A valley-seeking clustering principle is employed, requiring no a priori knowledge of the number of functional networks. The technique is applied to a data set acquired at rest and is shown to retrieve a number of identifiable functional networks. The method is proposed as an alternative to e. g. independent component analysis and exhibits an enhanced network separation capability and stability against noise.},
  author       = {Verdoolaege, Geert and Vlerick, Leslie and Achten, Eric},
  booktitle    = {IEEE International Conference on Image Processing ICIP},
  isbn         = {9781457713026},
  keyword      = {wavelet,fMRI,resting state,clustering},
  language     = {eng},
  location     = {Brussels, Belgium},
  pages        = {2717--2720},
  publisher    = {IEEE},
  title        = {Detection of resting-state brain activity in magnetic resonance images through wavelet feature cluster analysis},
  year         = {2011},
}

Chicago
Verdoolaege, Geert, Leslie Vlerick, and Eric Achten. 2011. “Detection of Resting-state Brain Activity in Magnetic Resonance Images Through Wavelet Feature Cluster Analysis.” In IEEE International Conference on Image Processing ICIP, 2717–2720. New York, NY, USA: IEEE.
APA
Verdoolaege, G., Vlerick, L., & Achten, E. (2011). Detection of resting-state brain activity in magnetic resonance images through wavelet feature cluster analysis. IEEE International Conference on Image Processing ICIP (pp. 2717–2720). Presented at the 18th IEEE International conference on Image Processing (ICIP 2011), New York, NY, USA: IEEE.
Vancouver
1.
Verdoolaege G, Vlerick L, Achten E. Detection of resting-state brain activity in magnetic resonance images through wavelet feature cluster analysis. IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE; 2011. p. 2717–20.
MLA
Verdoolaege, Geert, Leslie Vlerick, and Eric Achten. “Detection of Resting-state Brain Activity in Magnetic Resonance Images Through Wavelet Feature Cluster Analysis.” IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE, 2011. 2717–2720. Print.