Title :
A Normalized Framework for the Design of Feature Spaces Assessing the Left Ventricular Function
Author :
Garcia-Barnés, J. ; Gil, D. ; Badiella, L. ; Hernàndez-Sabaté, A. ; Carreras, F. ; Pujades, S. ; Martí, E.
Author_Institution :
Dept. of Comput. Sci., Univ. Autonoma de Barcelona, Bellaterra, Spain
fDate :
3/1/2010 12:00:00 AM
Abstract :
A through description of the left ventricle functionality requires combining complementary regional scores. A main limitation is the lack of multiparametric normality models oriented to the assessment of regional wall motion abnormalities (RWMA). This paper covers two main topics involved in RWMA assessment. We propose a general framework allowing the fusion and comparison across subjects of different regional scores. Our framework is used to explore which combination of regional scores (including 2-D motion and strains) is better suited for RWMA detection. Our statistical analysis indicates that for a proper (within interobserver variability) identification of RWMA, models should consider motion and extreme strains.
Keywords :
biomedical MRI; cardiology; image fusion; image motion analysis; image sequences; statistical analysis; RWMA detection; TMR sequences; feature spaces; fusion; interobserver variability; left ventricle functionality; multiparametric normality models; regional wall motion abnormalities; statistical analysis; tagged magnetic resonance; Capacitive sensors; Cardiac disease; Computer vision; Gas insulated transmission lines; Magnetic field measurement; Magnetic resonance; Magnetic resonance imaging; Motion detection; Myocardium; Statistical analysis; B-splines; bull´s eye plots; left ventricle; manifold parameterization; regional wall motion abnormalities; Adult; Algorithms; Female; Heart Ventricles; Humans; Magnetic Resonance Imaging; Male; Middle Aged; Models, Statistical; Myocardial Contraction; Observer Variation; ROC Curve; Reproducibility of Results; Sensitivity and Specificity; Ventricular Dysfunction, Left; Ventricular Function, Left;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2009.2034653