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Usefulness of fuzzy clustering for automated extraction of arterial input function for quantification of cerebral blood flow with dynamic susceptibility contrast-enhanced magnetic resonance imaging

✍ Scribed by M. Shinohara; K. Murase; T. Kitada; Y. Nishimura; Y. Yamazaki; S. Iwamoto; Y. Ueno; S. Yamada; K. Kikuchi; H. Miki; J. Ikezoe


Book ID
117549471
Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
34 KB
Volume
1230
Category
Article
ISSN
0531-5131

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Determination of arterial input function
✍ Kenya Murase; Keiichi Kikuchi; Hitoshi Miki; Teruhiko Shimizu; Junpei Ikezoe πŸ“‚ Article πŸ“… 2001 πŸ› John Wiley and Sons 🌐 English βš– 292 KB πŸ‘ 1 views

## Abstract An accurate determination of the arterial input function (AIF) is necessary for quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast‐enhanced magnetic resonance imaging. In this study, we developed a method for obtaining the AIF automatically using fuzzy c‐m

Measurement of arterial input functions
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## Abstract Measurement of the arterial input bolus shape is essential to the quantification of mean transit time and blood flow with dynamic susceptibility contrast (DSC) MRI. Input functions derived from the echoplanar signal intensity within or near arteries are highly nonlinear, yet such input