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IEEE Trans Med Imaging. 2006 Jan;25(1):62-73.

Cluster analysis of dynamic cerebral contrast-enhanced perfusion MRI time-series.

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  • 1Department of Electrical and Computer Engineering, Florida State University, Tallahassee, FL 32310-6046, USA.


We performed neural network clustering on dynamic contrast-enhanced perfusion magnetic resonance imaging time-series in patients with and without stroke. Minimal-free-energy vector quantization, self-organizing maps, and fuzzy c-means clustering enabled self-organized data-driven segmentation with respect to fine-grained differences of signal amplitude and dynamics, thus identifying asymmetries and local abnormalities of brain perfusion. We conclude that clustering is a useful extension to conventional perfusion parameter maps.

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