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Multiresolution fuzzy clustering of functional MRI data.
- Source :
-
Neuroradiology [Neuroradiology] 2003 Oct; Vol. 45 (10), pp. 691-9. Date of Electronic Publication: 2003 Aug 27. - Publication Year :
- 2003
-
Abstract
- Recent developments in the analysis of functional MRI data reveal a shift from hypothesis-driven statistical tests to unsupervised strategies. One of the most promising approaches is the fuzzy clustering algorithm (FCA), whose potential to detect activation patterns has already been demonstrated. But the FCA suffers from three drawbacks: first the computational complexity, second the higher sensitivity to noise and third the dependence on the random initialization. With the multiresolution approach presented here, these weak points are significantly improved, as is demonstrated in our tests with simulated and real functional MRI data.
- Subjects :
- Artifacts
Humans
Algorithms
Magnetic Resonance Imaging
Subjects
Details
- Language :
- English
- ISSN :
- 0028-3940
- Volume :
- 45
- Issue :
- 10
- Database :
- MEDLINE
- Journal :
- Neuroradiology
- Publication Type :
- Academic Journal
- Accession number :
- 12942214
- Full Text :
- https://doi.org/10.1007/s00234-003-1026-9