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A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also(More)
A novel framework to efficiently deal with three-dimensional (3-D) segmentation of challenging inhomogeneous data in real-time has been recently introduced by the authors. However, the existing framework still relied on manual initialization, which prevented taking full advantage of the computational speed of the method. In the present article, an automatic(More)
This paper describes a free open source software in Matlab (named Creaseg, http://www.creatis.insa-lyon. fr/∼bernard/creaseg) for the evaluation of the performance of different level-set based algorithms in the context of 2D image segmentation. The platform gives access to the implementation of six level-set methods that have been chosen in order to(More)
The segmentation of the myocardium in echocardiographic images is an important task for the diagnosis of heart disease. This task is difficult due to the inherent problems of echographic images (i.e. low contrast, speckle noise, signal dropout, presence of shadows). In this article, we propose a method to segment the whole myocardium (endocardial and(More)
In echocardiography, left ventricle detection is a common practice in order to retrieve indexes of myocardial health. Although a great attention has been given to the segmentation of the endocardium, very limited literature addresses the detection of both endo- and epicardial contours. Hereto, in this study we propose an original level-set technique(More)
Real-time 3D echocardiography (RT3DE) has already been shown to be an accurate tool for left ventricular (LV) volume assessment. However, LV border detection in RT3DE remains a time-consuming task jeopardizing the application of this modality in routine practice. We have recently developed a 3D automated segmentation framework (BEAS) able to capture the LV(More)