Abstract
Automating the analysis of left ventricular (LV) wall motion can improve objective prediction of coronary artery disease. A new method for classifying LV wall motion using shape models with localized variations was developed for this purpose. These sparse shape models were built from four-chamber and two-chamber echocardiographic sequences using principal component analysis and orthomax rotations. The resulting shape parameters were then used to classify wall-motion abnormalities of LV segments. Compared with the shape model before rotation, higher classification correctness was achieved using significantly less shape parameters. The local variations exhibited by these shape parameters correlated reasonably with the location of the segments.
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Leung, K.Y.E., Bosch, J.G. (2007). Local Wall-Motion Classification in Echocardiograms Using Shape Models and Orthomax Rotations. In: Sachse, F.B., Seemann, G. (eds) Functional Imaging and Modeling of the Heart. FIMH 2007. Lecture Notes in Computer Science, vol 4466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72907-5_1
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DOI: https://doi.org/10.1007/978-3-540-72907-5_1
Publisher Name: Springer, Berlin, Heidelberg
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