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9 May 2002 Fully automated endocardial contour detection in time sequences of echocardiograms by three-dimensional active appearance models
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Abstract
A novel 3-D Active Appearance Model (3-D AAM) is applied to fully automated endocardial contour detection in 2-D + time (2DT) 4-chamber ultrasound sequences, without knowledge of cardiac phase (ED/ES frames). 2DT appearance of the heart is modeled in 3-D by converting the stack of 2-D time slices into a 3-D voxel space. In a training set, an expert defines corresponding endocardial contour points for one complete cardiac cycle (ED to ED). 2DT shape is represented as a 3-D surface. Image appearance is modeled as a vector of voxel intensities in a volume-patch spanned by the 3-D surface. Principal Component Analysis extracts eigenvariations of 3-D shape and appearance, capturing typical cardiac motion patterns. 3-D AAM segments the image volume by minimizing 3-D model-to-target intensity differences, adjusting eigenvariation coefficients and 3-D pose using gradient descent minimization. This provides time-continuous border localization for one beat in both time and space. The method was used on 3-beat sequences from 129 patients split randomly into a training (65) and a test set (64). An independent expert manually drew all endocardial contours. 3-D AAM converged well in 89% of test cases. Average absolute temporal error was 37.0 msec, spatial error 3.35 mm, comparable to human inter-observer variabilities.
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Johan G. Bosch, Steven C. Mitchell, Boudewijn P. F. Lelieveldt, Francisca Nijland, Otto Kamp, Milan Sonka, and Johan H. C. Reiber "Fully automated endocardial contour detection in time sequences of echocardiograms by three-dimensional active appearance models", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467187
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