학술논문
Cluster analysis of dynamic cerebral contrast-enhanced perfusion MRI time-series
Document Type
Periodical
Source
IEEE Transactions on Medical Imaging IEEE Trans. Med. Imaging Medical Imaging, IEEE Transactions on. 25(1):62-73 Jan, 2006
Subject
Language
ISSN
0278-0062
1558-254X
1558-254X
Abstract
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.