Cerebral blood flow estimation from perfusion-weighted MRI using FT-based MMSE filtering method

Magnetic Resonance Imaging

Volumn 26, Issue 3, 2008, Pages 313-322

  Sakoglu, Unal ^a   Sood, Rohit ^a  

^a UNIVERSITY OF NEW MEXICO SCHOOL OF MEDICINE   (United States)

Author keywords

CBF; FT; MRI; Perfusion; SVD

Indexed keywords

ARTICLE; BRAIN BLOOD FLOW; COMPUTER SIMULATION; FOURIER TRANSFORMATION; MATHEMATICAL ANALYSIS; NOISE; NUCLEAR MAGNETIC RESONANCE IMAGING; PERFUSION WEIGHTED IMAGING; PRIORITY JOURNAL;

ALGORITHMS; BLOOD FLOW VELOCITY; CEREBROVASCULAR CIRCULATION; COMPUTER SIMULATION; CONTRAST MEDIA; FOURIER ANALYSIS; GADOLINIUM DTPA; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE ANGIOGRAPHY; REGIONAL BLOOD FLOW;

EID: 40049083411     PISSN: 0730725X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.mri.2007.08.007     Document Type: Article

References (15)

1. Albers G.W. Expanding the window for thrombolytic therapy in acute stroke. The potential role of acute MRI for patient selection. Stroke 30 10 (1999) 2230-2237
2. Zierler K.L. A simplified explanation of the theory of indicator-dilution for measurement of fluid flow and volume and other distributive phenomena. Bull Johns Hopkins Hosp 103 4 (1958) 199-217
3. Calamante F., Gadian D.G., and Connelly A. Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med 44 3 (2000) 466-473
4. Wirestam R., et al. Assessment of regional cerebral blood flow by dynamic susceptibility contrast MRI using different deconvolution techniques. Magn Reson Med 43 5 (2000) 691-700
5. Jerosch-Herold M., Swingen C., and Seethamraju R.T. Myocardial blood flow quantification with MRI by model-independent deconvolution. Med Phys 29 5 (2002) 886-897
6. Yeh C.K., Wang S.W., and Li P.C. Feasibility study of time-intensity-based blood flow measurements using deconvolution. Ultrason Imaging 23 2 (2001) 90-105
7. Murase K., Shinohara M., and Yamazaki Y. 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 12 (2001) 3147-3159
8. Wu O., et al. Effects of tracer arrival time on flow estimates in MR perfusion-weighted imaging. Magn Reson Med 50 4 (2003) 856-864
9. Ostergaard L., et al. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med 36 5 (1996) 715-725
10. Ostergaard L., et al. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results. Magn Reson Med 36 5 (1996) 726-736
11. Barbier E.L., Lamalle L., and Decorps M. Methodology of brain perfusion imaging. J Magn Reson Imaging 13 4 (2001) 496-520
12. Liu H.L., et al. Cerebral blood flow measurement by dynamic contrast MRI using singular value decomposition with an adaptive threshold. Magn Reson Med 42 1 (1999) 167-172
13. Oppenheim A.V., Willsky A.S., and Hamid N.S. Signals and systems. 2nd ed. (1996), Prentice Hall, Upper Saddle River (NJ)
14. Gudbjartsson H., and Patz S. The Rician distribution of noisy MRI data. Magn Reson Med 34 6 (1995) 910-914
15. Salluzzi M., Frayne R., and Smith M.R. An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies. Magn Reson Imaging 23 3 (2005) 481-492