DocumentCode :
911095
Title :
Reproducible Classification of Infarct Heterogeneity Using Fuzzy Clustering on Multicontrast Delayed Enhancement Magnetic Resonance Images
Author :
Detsky, J.S. ; Paul, Gideon ; Dick, Alexander J. ; Wright, Graham A.
Author_Institution :
Imaging Res., Sunnybrook Health Sci. Centre, Toronto, ON, Canada
Volume :
28
Issue :
10
fYear :
2009
Firstpage :
1606
Lastpage :
1614
Abstract :
Delayed enhancement MRI (DE-MRI) can be used to identify myocardial infarct (MI). Classification of MI into the infarct core and heterogeneous periphery (called the gray zone) on conventional inversion-recovery gradient echo (IR-GRE) DE-MRI images has been related to inducibility for ventricular tachycardia. However, this classification is sensitive to image noise, depends on the signal intensity characteristics in a remote region of myocardium, and requires manual contours of the endocardial border. Image analysis and fuzzy clustering techniques were developed to analyze images acquired using a multicontrast delayed enhancement (MCDE) sequence in order characterize the infarct zones. The MCDE analysis is automated and uses data fitting of signal intensities acquired at multiple inversion times. In a study of 15 patients with chronic MI, the gray zones derived from IR-GRE and MCDE images were comparable. The variability in the gray zone size associated with random noise and operator input was significantly reduced using the MCDE-based analysis compared to the IR-GRE-based analysis. In summary, the MCDE approach yields a more reproducible measure of the infarct core and gray zones on any given data set.
Keywords :
biomedical MRI; cardiology; diseases; fuzzy set theory; image classification; image denoising; image enhancement; medical image processing; muscle; pattern clustering; delayed enhancement MRI; fuzzy clustering; gray zones; image analysis; image classification; image enhancement; image noise; inversion-recovery gradient echo; magnetic resonance imaging; multicontrast delayed enhancement; myocardial infarct; random noise; ventricular tachycardia; Biomedical imaging; Biophysics; Blood; Delay; Image segmentation; Image sequence analysis; Magnetic cores; Magnetic resonance; Magnetic resonance imaging; Myocardium; Classification; delayed enhancement; fuzzy clustering; myocardial infarction; Aged; Algorithms; Cluster Analysis; Computer Simulation; Fuzzy Logic; Heart; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Imaging; Male; Middle Aged; Myocardial Infarction; Regression Analysis; Reproducibility of Results;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2009.2023515
Filename :
4967967
Link To Document :
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