Johannes G Bosch

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A novel extension of active appearance models (AAMs) for automated border detection in echocardiographic image sequences is reported. The active appearance motion model (AAMM) technique allows fully automated robust and time-continuous delineation of left ventricular (LV) endocardial contours over the full heart cycle with good results. Nonlinear intensity(More)
A model-based method for three-dimensional image segmentation was developed and its performance assessed in segmentation of volumetric cardiac magnetic resonance (MR) images and echocardiographic temporal image sequences. Comprehensive design of a three-dimensional (3-D) active appearance model (AAM) is reported for the first time as an involved extension(More)
A fully automated approach to segmentation of the left and right cardiac ventricles from magnetic resonance (MR) images is reported. A novel multistage hybrid appearance model methodology is presented in which a hybrid active shape model/active appearance model (AAM) stage helps avoid local minima of the matching function. This yields an overall more(More)
Ultrasound can be used to study tendon movement. However, measurement of tendon movement is mostly based on manual tracking of anatomical landmarks such as the musculo-tendinous junction, limiting the applicability to a small number of muscle-tendon units. The aim of this study was to quantify tendon displacement without anatomical landmarks using a speckle(More)
RATIONALE AND OBJECTIVE Shape analysis of endocardial contour sequences from echocardiograms can provide classification of wall motion abnormalities (WMA). MATERIALS AND METHODS We previously reported on active appearance motion models (AAMM) for automated detection of endocardial contours in sequences of echocardiograms. The shape analysis of AAMM(More)
Automated segmentation approaches for the left ventricle (LV) in 3-D echocardiography (3DE) often rely on manual initialization. So far, little effort has been put into automating the initialization procedure to get to a fully automatic segmentation approach. We propose a fully automatic method for the detection of the LV long axis (LAX) and the mitral(More)
Many segmentation methods for thoracic volume data require manual input in the form of a seed point, initial contour, volume of interest etc. The aim of the work presented here is to further automate this segmentation initialization step. In this paper an anatomical modeling and matching method is proposed to coarsely segment thoracic volume data into(More)
The analysis of echocardiograms, whether visual or automated, is often hampered by ultrasound artifacts which obscure the moving myocardial wall. In this study, a probabilistic framework for tracking the endocardial surface in 3D ultrasound images is proposed, which distinguishes between visible and artifact-obscured myocardium. Motion estimation of visible(More)