A normalized framework for the design of feature spaces assessing the left ventricular function.
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.
Garcia-Barnes
J
J
Computer Vision Center and the Department of Computer Sciences, Universitat Autonoma de Barcelona, 08193 Bellaterra, Spain. jaumegb@cvc.uab.cat
Gil
D
D
Badiella
L
L
Hernandez-Sabate
A
A
Carreras
F
F
Pujades
S
S
Marti
E
E
D000328:Adult; D000465:Algorithms; D005260:Female; D006352:Heart Ventricles / Q000503:physiopathology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D009200:Myocardial Contraction / Q000502:physiology; D015588:Observer Variation; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000175:diagnosis / Q000503:physiopathology*; D016277:Ventricular Function, Left / Q000502:physiology*