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The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Perfusion Imaging Using Arterial Spin Labeling

Golay, Xavier, Hendrikse, Jeroen, Lim, Tchoyoson C. C.·2004·Topics in Magnetic Resonance Imaging

Abstract

Arterial spin labeling is a magnetic resonance method for the measurement of cerebral blood flow. In its simplest form, the perfusion contrast in the images gathered by this technique comes from the subtraction of two successively acquired images: one with, and one without, proximal labeling of arterial water spins after a small delay time. Over the last decade, the method has moved from the experimental laboratory to the clinical environment. Furthermore, numerous improvements, ranging from new pulse sequence implementations to extensive theoretical studies, have broadened its reach and extended its potential applications. In this review, the multiple facets of this powerful yet difficult technique are discussed. Different implementations are compared, the theoretical background is summarized, and potential applications of various implementations in research as well as in the daily clinical routine are proposed. Finally, a summary of the new developments and emerging techniques in this field is provided.

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Metadata

Authors
Golay, X., Hendrikse, J., & Lim, T. C. C.
Venue
Topics in Magnetic Resonance Imaging
Published
2004-02
Volume
15
Issue
1
Pages
10-27
ISSN
0899-3459 (ISSN-L)
OpenAlex
W2076212130
Cited by
256
References
7
FWCI
11.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Perfusion Imaging Using Arterial Spin Labeling. https://app.cochat.ai/papers/10.1097/00002142-200402000-00003
The paper
Golay, X., Hendrikse, J., & Lim, T. C. C. (2004). Perfusion Imaging Using Arterial Spin Labeling. Topics in Magnetic Resonance Imaging. https://doi.org/10.1097/00002142-200402000-00003

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.