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Support Vector Analysis of Color-Doppler Images: A New Approach for Estimating Indices on Left Ventricular Function

dc.contributor.authorRojo-Álvarez, José Luis
dc.contributor.authorBermejo, Javier
dc.contributor.authorJuárez Caballero, Víctor Manuel
dc.contributor.authorYotti, Raquel
dc.contributor.authorCortina, Cristina
dc.contributor.authorGarcía Fernández, Miguel Ángel
dc.contributor.authorAntoranz, José Carlos
dc.description.abstractReliable noninvasive estimators of global left ventricular (LV) chamber function remain unavailable. We have previously demonstrated a potential relationship between color-Doppler M-mode (CDMM) images and two basic indices of LV function: peak-systolic elastance (Emax) and the time-constant of LV relaxation (tau). Thus, we hypothesized that these two indices could be estimated noninvasively by adequate postprocessing of CDMM recordings. A semiparametric regression (SR) version of support vector machine (SVM) is here proposed for building a blind model, capable of analyzing CDMM images automatically, as well as complementary clinical information. Simultaneous invasive and Doppler tracings were obtained in nine mini-pigs in a high-fidelity experimental setup. The model was developed using a test and validation leave-one-out design. Reasonably acceptable prediction accuracy was obtained for both Emax (intraclass correlation coefficient 0.81) and ( 0. 61). For the first time, a quantitative, noninvasive estimation of cardiovascular indices is addressed by processing Doppler-echocardiography recordings using a learning-from-samples
dc.relation.ispartofseriesIEEE Transactions on Medical Imaginges
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.titleSupport Vector Analysis of Color-Doppler Images: A New Approach for Estimating Indices on Left Ventricular Functiones
dc.subject.unesco32 Ciencias Médicases
dc.description.departamentoTeoría de la Señal y Comunicaciones

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Atribución-NoComercial-SinDerivadas 3.0 EspañaExcept where otherwise noted, this item's license is described as Atribución-NoComercial-SinDerivadas 3.0 España