Assessment of Cerebral Blood Flow, Volume, and Mean Transit Time from Bolus-Tracking MRI Images: Theory and Practice - Advance Image Processing in Magnetic Resonance Imaging - page 588

23. Calamante, F., Gadian, D.G., and Connelly, A. (2000). Delay and dispersion effects

in dynamic susceptibility contrast MRI: simulations using singular value decom-
position. Magn. Reson. Med . 44: 466-473.

24. Calamante, F., Gadian, D.G., and Connelly, A. (2002). Quantification of perfusion

using bolus tracking magnetic resonance imaging in stroke: assumptions, limita-
tions, and potential implications for clinical use. Stroke 33: 1146-1151.

25. Alsop, D.C. and Detre, J.A. (1996). Reduced transit-time sensitivity in noninvasive

magnetic resonance imaging of human cerebral blood flow. J. Cereb. Blood Flow
Metab . 16: 1236-1249.

26. van Osch, M.J., Vonken, E.J., Wu, O., Viergever, M.A., van der Grond, J., and

Bakker, C.J. (2003). Model of the human vasculature for studying the influence
of contrast injection speed on cerebral perfusion MRI. Magn. Reson. Med . 50:
614-622.

27. Larson, K.B., Perman, W.H., Perlmutter, J.S., Gado, M.H., and Zierler, K.L.

(1994). Tracer-kinetic analysis for measuring regional cerebral blood flow by
dynamic nuclear magnetic resonance imaging. J. Theor. Biol . 170: 1-14.

28. Ostergaard, L., Chesler, D.A., Weisskoff, R.M., Sorensen, A.G., and Rosen, B.R.

(1999). Modeling cerebral blood flow and flow heterogeneity from magnetic
resonance residue data. J. Cereb. Blood Flow Metab . 19: 690-699.

29. Kroll, K., Wilke, N., Jerosch-Herold, M., Wang, Y., Zhang, Y., Bache, R.J., and

Bassingthwaighte, J.B. (1996). Modeling regional myocardial flows from residue
functions of an intravascular indicator. Am. J. Physiol . 271: H1643-H1655.

30. Smith, A.M., Grandin, C.B., Duprez, T., Mataigne, F., and Cosnard, G. (2000).

Whole brain quantitative CBF and CBV measurements using MRI bolus tracking:
comparison of methodologies. Magn. Reson. Med . 43: 559-564.

31. De Nicolao, G., Sparacino, G., and Cobelli, C. (1997). Nonparametric input

estimation in physiological systems: Problems, methods, and case studies. Auto-
matica 33: 851-870.

32. Murase, K., Shinohara, M., and Yamazaki, Y. (2001). Accuracy of deconvolution

analysis based on singular value decomposition for quantification of cerebral blood
flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging.
Phys. Med. Biol . 46: 3147-3159.

33. Liu, H.L., Pu, Y., Liu, Y., Nickerson, L., Andrews, T., Fox, P.T., and Gao, J.H.

(1999). Cerebral blood flow measurement by dynamic contrast MRI using singular
value decomposition with an adaptive threshold. Magn. Reson. Med . 42: 167-172.

34. Wirestam, R., Andersson, L., Ostergaard, L., Bolling, M., Aunola, J.P., Lindgren,

A., Geijer, B., Holtas, S., and Stahlberg, F. (2000). Assessment of regional cerebral
blood flow by dynamic susceptibility contrast MRI using different deconvolution
techniques. Magn. Reson. Med . 43: 691-700.

35. Sourbron, S., Luypaert, R., Van Schuerbeek, P., Dujardin, M., Stadnik, T., and Osteaux,

M. (2004). Deconvolution of dynamic contrast-enhanced MRI data by linear inversion:
choice of the regularization parameter. Magn. Reson. Med . 52: 209-213.

36. Wu, O., Ostergaard, L., Weisskoff, R.M., Benner, T., Rosen, B.R., and Sorensen,

A.G. (2003). Tracer arrival timing-insensitive technique for estimating flow in MR
perfusion-weighted imaging using singular value decomposition with a block-
circulant deconvolution matrix. Magn. Reson. Med . 50: 164-174.

37. Smith, M.R., Lu, H., Trochet, S., and Frayne, R. (2004). Removing the effect of

SVD algorithmic artifacts present in quantitative MR perfusion studies. Magn.
Reson. Med . 51: 631-634.