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RATIONALE AND OBJECTIVES Segmentation of the left ventricle (LV) is very important in the assessment of cardiac functional parameters. The aim of this study is to develop a novel and robust algorithm which can improve the accuracy of automatic LV segmentation on short-axis cardiac magnetic resonance images (MRI). MATERIALS AND METHODS The database used in(More)
Segmentation of the left ventricle from cardiac magnetic resonance images (MRI) is very important to quantitatively analyze global and regional cardiac function. The aim of this study is to develop a novel and robust algorithm which can improve the accuracy of automatic left ventricle segmentation on short-axis cardiac MRI. The database used in this study(More)
Segmentation of the left ventricle is very important to quantitatively analyze global and regional cardiac function from magnetic resonance. The aim of this study is to develop a novel algorithm for segmenting left ventricle on short-axis cardiac magnetic resonance images (MRI) to improve the performance of computer-aided diagnosis (CAD) systems. In this(More)
We develop an effective method for the study of cervical vertebra maturation (CVM) for bone age evaluation. Such studies need an accurate X-ray radiographs segmentation of cervical vertebra. It is difficult to have a good segmentation on this type of images. Current segmentation methods do not work well on scanned images from analog image X-ray radiographs(More)
In the segmentation of cardiac tagging magnetic resonance (tMR) images, it is difficult to segment the left ventricle automatically by using the traditional segmentation model because of the interference caused by the tags. A new snake model based on hybrid gradient vector flow (HGVF) is proposed by us to improve this segmentation. Due to the different(More)
We develop an effective method for improving the segmentation result based on the Multi-Stencils Fast Marching method (MSFM). In MSFM, the gradient information of the image plays a vital role for calculating edges. It is straightforward to obtain the edge of good quality images; however, MSFM may not have robust edge maps available for images with spurious(More)
In order to accurately extract the endocardium and epicardium of the left ventricle from cardiac magnetic resonance (MR) images, a method based on developed Otsu and dynamic programming has been proposed. First, regions with high gray value are divided into several left ventricle candidate regions by the developed Otsu algorithm, which based on constraining(More)
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