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Retinal blood vessel detection is very significant in the disease diagnosis made by ophthalmologists. Thus, an automated method to segment the blood vessels in retinal images is proposed using the hessian-based filter and random walk algorithms. The aim of the hessian-based vascular filtering is to enhance the vessel structures. Local thresholding is also used to obtain seed groups for the random...
Segmentation of the retina vessels plays an important role in detecting earlier diseases, i.e. diabetic and hypertension. These diseases may cause the shape change of the vasculature. Due to the inhomogeneous of the retina image, it's very difficult to use region static information to get the result. We use a new level set method based on local region cluster information which proves to be well performed...
Medical image registration methods based on the maximization of mutual information have shown promising results. But it needs much computing time. This paper presents a new method to rigid registration based on the combination of scale images and mutual information. Firstly, the concept of area morphology is introduced. And then, the scale images are constructed with the area morphological operators...
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