The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Model‐free arterial spin labeling quantification approach for perfusion MRI
Open accessAbstract
In this work a model‐free arterial spin labeling (ASL) quantification approach for measuring cerebral blood flow (CBF) and arterial blood volume (aBV) is proposed. The method is based on the acquisition of a train of multiple images following the labeling scheme. Perfusion is obtained using deconvolution in a manner similar to that of dynamic susceptibility contrast (DSC) MRI. Local arterial input functions (AIFs) can be estimated by subtracting two perfusion‐weighted images acquired with and without crusher gradients, respectively. Furthermore, by knowing the duration of the bolus of tagged arterial blood, one can estimate the aBV on a voxel‐by‐voxel basis. The maximum of the residue function obtained from the deconvolution of the tissue curve by the AIF is a measure of CBF after scaling by the locally estimated aBV. This method provides averaged gray matter (GM) perfusion values of 38 ± 2 ml/min/100 g and aBV of 0.93% ± 0.06%. The average CBF value is 10% smaller than that obtained on the same data set using the standard general kinetic model (42 ± 2 ml/min/100 g). Monte Carlo simulations were performed to compare this new methodology with parametric fitting by the conventional model. Magn Reson Med, 2006. © 2006 Wiley‐Liss, Inc.
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A Computational Approach to Edge Detection
Canny, J. (1986) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1986.4767851 · Cited by 30,004
Numerical recipes in C: the art of scientific computing
(1993) · Choice Reviews Online · doi:10.5860/choice.30-5638 · Cited by 17,933
The Levenberg-Marquardt algorithm: Implementation and theory
Moré, J. J. (1978) · Lecture Notes in Mathematics · doi:10.1007/bfb0067700 · Cited by 5,773
Kety, S. S., & Schmidt, C. F. (1948) · Journal of Clinical Investigation · doi:10.1172/jci101994 · Cited by 2,059
Automated Image Registration: I. General Methods and Intrasubject, Intramodality Validation
Woods, R. P., Grafton, S. T., Holmes, C. J., Cherry, S. R., & Mazziotta, J. C. (1998) · Journal of Computer Assisted Tomography · doi:10.1097/00004728-199801000-00027 · Cited by 1,707
Magnetic resonance imaging of perfusion using spin inversion of arterial water.
Williams, D. S., Detre, J. A., Leigh, J. S., & Koretsky, A. P. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.1.212 · Cited by 1,546
Østergaard, L., Weisskoff, R. M., Chesler, D. A., Gyldensted, C., & Rosen, B. R. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910360510 · Cited by 1,512
On the Theory of the Indicator-Dilution Method for Measurement of Blood Flow and Volume
Meier, P., & Zierler, K. L. (1954) · Journal of Applied Physiology · doi:10.1152/jappl.1954.6.12.731 · Cited by 1,274
A general kinetic model for quantitative perfusion imaging with arterial spin labeling
Buxton, R. B., Frank, L. R., Wong, E. C., Siewert, B., Warach, S., & Edelman, R. R. (1998) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910400308 · Cited by 1,263
Numerical recipes in C (2nd ed.): the art of scientific computing
Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery, B. P. (1992) · Cambridge University Press eBooks · Cited by 1,156
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Metadata
- Authors
- Petersen, E. T., Lim, T., & Golay, X.
- Venue
- Magnetic Resonance in Medicine
- Publisher
- Wiley
- Published
- 2006-01-13
- Volume
- 55
- Issue
- 2
- Pages
- 219-232
- ISSN
- 0740-3194 (ISSN-L)
- 1522-2594
- OpenAlex
- W2057746943
- Cited by
- 305
- References
- 35
- FWCI
- 8.82
- Type
- journal article
- Language
- en
- Open access
- bronze
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