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dc.contributor.authorMedina Molina, Ruben-
dc.contributor.authorMorocho Zurita, Carlos Villie-
dc.contributor.authorVanegas Peralta, Pablo Fernando-
dc.date.accessioned2018-01-11T16:47:51Z-
dc.date.available2018-01-11T16:47:51Z-
dc.date.issued2016-06-01-
dc.identifier.issn15480992-
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84986203455&doi=10.1109%2fTLA.2016.7555259&partnerID=40&md5=4cc1d8c4acf1d0e80f1c3f8e88d13c9f-
dc.identifier.urihttp://dspace.ucuenca.edu.ec/handle/123456789/29253-
dc.description.abstractThis paper reports an optical based method for quantification of cardiac motion in MRI images. The cardiac motion is quantified in a Short-Axis (SAX) slice located at the mid-cavity of the left ventricle. In this slice, the left ventricle wall is segmented for extracting the endocardium, the epicardium and the midwall. The velocity field for these contours is available after performing the optical flow estimation for the given slice. Post-processing of this motion field enables estimation of the radial displacement. The core of this cardiac motion quantification method is a sparse based algorithm for optical flow estimation. This algorithm is presented and compared with several classical optical flow estimation algorithms. The comparison is performed using several video sequences available from the Middlebury benchmark where the ground truth optical flow is known. The algorithms with better performance are also tested using a 4 D cardiac Magnetic Resonance Image (MRI) sequence. Results show that he sparse algorithm estimates an optical flow field that represents the motion of contraction during the systole interval. Moreover, results about radial displacement estimation on real MRI sequences for a normal subject and a patient with hypertrophy show that the proposed quantification method could be useful for quantification of left ventricle motion.-
dc.language.isoen_US-
dc.publisherIEEE COMPUTER SOCIETY-
dc.sourceIEEE Latin America Transactions-
dc.subjectCardiac Motion-
dc.subjectLeft Ventricle-
dc.subjectMagnetic Resonance Imaging-
dc.subjectMedical Imaging-
dc.subjectOptical Flow-
dc.subjectSparse Methods-
dc.titleCardiac Motion Estimation in Magnetic Resonance Images Using Optical Flow-
dc.typeArticle-
dc.ucuenca.idautor102520123-
dc.ucuenca.idautor0300930328-
dc.ucuenca.idautor0102274891-
dc.identifier.doi10.1109/TLA.2016.7555259-
dc.ucuenca.embargoend2022-01-01 0:00-
dc.ucuenca.afiliacionmedina, r., departamento de ingenieriá eléctrica, electrónica y de telecomunicaciones, facultad de ingenieriá, universidad de cuenca, ecuador-
dc.ucuenca.afiliacionmorocho, v., departamento de ciencias de la computación, facultad de ingenieriá, universidad de cuenca, ecuador-
dc.ucuenca.afiliacionvanegas, p., departamento de ciencias de la computación, facultad de ingenieriá, universidad de cuenca, ecuador-
dc.ucuenca.volumen14-
dc.ucuenca.indicebibliograficoSCOPUS-
dc.ucuenca.factorimpacto0.247-
dc.ucuenca.cuartilQ2-
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