Classification of segmental wall motion in echocardiography using quantified parametric images

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Abstract

The interpretation of cine-loops and parametric images to assess regional wall motion in echocardiography requires to acquire an expertise, which is based on training. To overcome the training phase for the interpretation of new parametric images, a quantification based on profiles in the parametric images was attempted. The classification of motion was performed on a training set including 362 segments and tested on a second database including 238 segments. The consensual visual interpretation of two-dimensional sequences by two experienced readers were used as the "gold standard". Mono- and multi-parametric classification approaches were undertaken. Results show an accuracy of 74% for training and 68% for test in case of mono-parametric approach. They are 80% and 67% in case of multi-parametric approach. Moreover, the evaluation protocol enables to understand the limitations of this approach. The in-depth study shows that a large part of false-positive segments are apical segments. This suggests that taking into account the segment location could improve the performances. © Springer-Verlag Berlin Heidelberg 2005.

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APA

Dominguez, C. R., Kachenoura, N., Mulé, S., Tenenhaus, A., Delouche, A., Nardi, O., … Frouin, F. (2005). Classification of segmental wall motion in echocardiography using quantified parametric images. In Lecture Notes in Computer Science (Vol. 3504, pp. 477–486). Springer Verlag. https://doi.org/10.1007/11494621_47

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