TY - GEN
T1 - Spatiotemporal denoising and clustering of fMRI data
AU - Song, Xiaomu
AU - Murphy, Matthew
AU - Wyrwicz, Alice M.
PY - 2006
Y1 - 2006
N2 - This paper examines combined spatiotemporal denoising and clustering of functional magnetic resonance imaging (fMRI) time series. Most fMRI denoising methods are implemented either in spatial or temporal domain without taking into account both space and time information. In this work, a spatiotemporal denoising method is developed where spatial denoising is implemented by Bayesian shrinkage that uses temporal prior information obtained by statistical testing on all voxel time courses. After the denoising, a set of spatiotemporal features are extracted and characterized by a Gaussian mixture model, which is applied to detect activated areas. The proposed methods have been tested on both synthetic and experimental data, and the results demonstrate their effectiveness.
AB - This paper examines combined spatiotemporal denoising and clustering of functional magnetic resonance imaging (fMRI) time series. Most fMRI denoising methods are implemented either in spatial or temporal domain without taking into account both space and time information. In this work, a spatiotemporal denoising method is developed where spatial denoising is implemented by Bayesian shrinkage that uses temporal prior information obtained by statistical testing on all voxel time courses. After the denoising, a set of spatiotemporal features are extracted and characterized by a Gaussian mixture model, which is applied to detect activated areas. The proposed methods have been tested on both synthetic and experimental data, and the results demonstrate their effectiveness.
KW - Bayesian shrinkage
KW - Functional magnetic resonance imaging
KW - Gaussian mixture model
KW - Wavelet
UR - http://www.scopus.com/inward/record.url?scp=78649813939&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78649813939&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2006.313025
DO - 10.1109/ICIP.2006.313025
M3 - Conference contribution
AN - SCOPUS:78649813939
SN - 1424404819
SN - 9781424404810
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2857
EP - 2860
BT - 2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
T2 - 2006 IEEE International Conference on Image Processing, ICIP 2006
Y2 - 8 October 2006 through 11 October 2006
ER -