First-pass myocardial perfusion image registration by maximization of normalized mutual information

Journal of Magnetic Resonance Imaging

Volumn 27, Issue 3, 2008, Pages 529-537

  Wong, Kelvin K ^a   Yang, Edward S ^b   Wu, Ed X ^b   Tse, Hung Fat ^b   Wong, Stephen T ^a  

^a HOUSTON METHODIST HOSPITAL   (United States)

^b UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

MR myocardial perfusion registration; Normalized mutual information; Quantitative perfusion analysis

Indexed keywords

ADENOSINE; GADOLINIUM PENTETATE MEGLUMINE;

ADULT; ARTICLE; BONE MARROW CELL; CLINICAL ARTICLE; HEART LEFT VENTRICLE; HEART MUSCLE PERFUSION; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; MONONUCLEAR CELL; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS;

ALGORITHMS; BONE MARROW TRANSPLANTATION; HEART VENTRICLES; HUMANS; MAGNETIC RESONANCE ANGIOGRAPHY; MIDDLE AGED;

EID: 40449137625     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.21254     Document Type: Article

References (25)

1. Al-Saadi N, Nagel E, Gross M, et al. Improvement of myocardial perfusion reserve early after coronary intervention: assessment with cardiac magnetic resonance imaging. J Am Coll Cardiol 2000:36:1557-1564.
2. Ito H, Tomooka T, Sakai N, et al. Lack of myocardial perfusion immediately after successful thrombolysis. A predictor of poor recovery of left ventricular function in anterior myocardial infarction. Circulation 1992:85:1699-1705.
3. Sciagra R, Parodi G, Pupi A, et al. Gated SPECT evaluation of outcome after abciximab-supported primary infarct artery stenting for acute myocardial infarction: the scintigraphic data of the abciximab and carbostent evaluation (ACE) randomized trial. J Nucl Med 2005:46:722-727.
4. Wilke N, Jerosch-Herold M, Wang Y, et al. Myocardial perfusion reserve: assessment with multisection, quantitative, first-pass MR imaging. Radiology 1997:204:373-384.
5. Panting JR, Gatehouse PD, Yang GZ, et al. Abnormal subendocardial perfusion in cardiac syndrome X detected by cardiovascular magnetic resonance imaging. N Engl J Med 2002:346:1948-1953.
6. Wilke N, Simm C, Zhang J, et al. Contrast-enhanced first pass myocardial perfusion imaging: correlation between myocardial blood flow in dogs at rest and during hyperemia. Magn Reson Med 1993:29:485-497.
7. Fischer SE, Wickline SA, Lorenz CH. Novel real-time R-wave detection algorithm based on the vectorcardiogram for accurate gated magnetic resonance acquisitions. Magn Reson Med 1999:42:361-370.
8. Bansal R, Funka-Lea G. Integrated image registration for cardiac MR perfusion data. In: Lecture notes in computer science. Vol. 2488. Berlin: Springer; 2002. p 659-666.
9. Dornier C, Ivancevic MK, Thevenaz P, Vallee JP. Improvement in the quantification of myocardial perfusion using an automatic spline-based registration algorithm. J Magn Reson Imaging 2003:18:160-168.
10. Gupta SN, Solaiyappan M, Beache GM, Aral AE, Foo TK. Fast method for correcting image misregistration due to organ motion in time-series MRI data. Magn Reson Med 2003:49:506-514.
11. Gallippi CM, Kramer CM, Hu YL, Vido DA, Reichek N, Rogers WJ. Fully automated registration and warping of contrast-enhanced first-pass perfusion images. J Cardiovasc Magn Reson 2002:4:459-469.
12. Bidaut LM, Vallee JP. Automated registration of dynamic MR images for the quantification of myocardial perfusion. J Magn Reson Imaging 2001:13:648-655.
13. Stegmann MB, Olafsdottir H, Larsson HB. Unsupervised motion-compensation of multi-slice cardiac perfusion MRI. Med Image Anal 2005:9:394-410.
14. Kawakami K, Murase K, Kumashiro M, et al. Automatic motion correction for quantification of myocardial perfusion with dynamic magnetic resonance imaging. Magn Reson Med Sci 2004:3:105-117.
15. Delzescaux T, Frouin F, De Cesare A, et al. Adaptive and self-evaluating registration method for myocardial perfusion assessment. Magma 2001:13:28-39.
16. Wong KK, Wu EX, Tse HF, Yang ES. Myocardial perfusion image registration using normalized mutual information. In: Proceedings of the 13th Annual Meeting of ISMRM, Miami, 2005. (abstract 2788).
17. Bracoud L, Vincent F, Pachai C, Canet E, Croisille P, Revel D. Automatic registration of MR first-pass myocardal perfusion images. In: Lecture notes in computer science. Vol. 2674. Berlin: Springer; 2003. p 215-223.
18. Wells WM III, Viola P, Atsumi H, Nakajima S, Kikinis R. Multi-modal volume registration by maximization of mutual information. Med Image Anal 1996:1:35-51.
19. Studholme C, Hill DLG, Hawkes DJ. An overlap invariant entrophy measure of 3D medical image alignment. Pattern Recognit 1999:32:71-86.
20. Maes F, Collignon A, Vandermeulen D, Marchal G, Suetens P. Multimodality image registration by maximization of mutual information. IEEE Trans Med Imaging 1997:16:187-198.
21. Tse HF, Kwong YL, Chan JK, Lo G, Ho CL, Lau CP. Angiogenesis in ischaemic myocardium by intramyocardial autologous bone marrow mononuclear cell implantation. Lancet 2003:361:47-49.
22. Tse HF, Thambar S, Kwong YL, et al. Safety of catheter-based intramyocardial autologous bone marrow cells implantation for therapeutic angiogenesis. Am J Cardiol 2006:98:60-62.
23. Jerosch-Herold M, Seethamraju RT, Swingen CM, Wilke NM, Stillman AE. Analysis of myocardial perfusion MRI. J Magn Reson Imaging 2004:19:758-770.
24. Zhu YM, Cochoff SM. Influence of implementation parameters on registration of MR and SPECT brain images by maximization of mutual information. J Nucl Med 2002:43:160-166.
25. Ritter C, Brackertz A, Sandstede J, Beer M, Hahn D, Kostler H. Absolute quantification of myocardial perfusion under adenosine stress. Magn Reson Med 2006:56:844-849.