Virtual M-Mode for Echocardiography: A New Approach for the Segmentation of the Anterior Mitral Leaflet
; Costa, E.
; Veiga, D.
; Ferreira, M. J. Ferreira
; Mattos, S. S.
IEEE Journal of Biomedical and Health Informatics Vol. ., Nº ., pp. . - ., January, 2018.
ISSN (print): 2168-2208
ISSN (online): 2168-2194
Scimago Journal Ranking: 1,12 (in 2018)
Digital Object Identifier: 10.1109/JBHI.2018.2799738
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Rheumatic heart disease can result from repeated episodes of acute rheumatic fever, which damages the heart valves and reduces their functionality. Early manifestations of heart valve damage are visible in echocardiography in the form of valve thickening, shape changing and mobility reduction. The quantification of these features is important for a precise diagnosis and it is the main motivation for this work. The first step to make this quantification is to accurately identify and track the anterior mitral leaflet throughout the cardiac cycle. An accurate segmentation and tracking with minimum user interaction is still an open problem in literature due to low image quality, speckle noise, signal dropout and non-rigid deformations. In this work, we propose a novel approach for the identification of the anterior mitral valve leaflet in all frames. The method requires a single user-specified point on the posterior wall of the aorta as input, in the first frame. The echocardiography videos are converted into a new image space, the Virtual M-mode, which samples the original echocardiography image over automatically estimated scanning lines. This new image space not only provides the motion pattern of the posterior wall of the aorta, the anterior wall of the aorta and the posterior wall of the left atrium, but also provides the location of the structures in each frame. The location information is then used to initialize the localized active contours, followed by segmenting the anterior mitral leaflet. Results shown that the new image space has robustly identified the anterior mitral valve leaflet, without any failure. The median modified Hausdorff distance error of the proposed method was 2.3 mm, with a recall of 0.94.