title: Artificial vision approach to the understanding of heart motion.
abstract: To overcome the major drawbacks of conventional descriptive methods, we have developed a computer vision approach to aid understanding of heart motion from a series of sequential X-ray images. The computation is addressed of local descriptors of the heart pumping function from ventricular contours. Physical constraints are exploited such as spatial smoothness of the displacement field and shape correspondence between ventricular boundaries during the beat. A computational method is proposed for the estimation of the displacement field of the left ventricular boundary. Moreover, the spatial arrangement of the estimated motion field is rendered explicit so that it may be utilized in the medical clinic (or for high-level symbolic processing). This is achieved using a grouping criterion which allows the clustering of contiguous points of the left ventricular outline into curve segments which have homogeneous motion properties.
authors.affiliation: C.N.R. Institute of Clinical Physiology, Pisa, Italy.
authors.forename: G
authors.initials: G
authors.lastname: Coppini
authors.forename: M
authors.initials: M
authors.lastname: Demi
authors.forename: R
authors.initials: R
authors.lastname: Calamai
authors.forename: G
authors.initials: G
authors.lastname: Valli
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009200:Myocardial Contraction / Q000502:physiology*; D016277:Ventricular Function, Left / Q000502:physiology