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This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, using group sparsity. Because of the large variations in image appearance due to changes of illumination, specular reflections and other visual noise, the two classes have a strong overlap in feature space, whether features...
In this paper, an automated retinal vessel extraction algorithm is represented. A multi-scale morphological algorithm is used for local contrast enhancement of color retinal image. This method enhances vessels not only in color image, but also in the three color components of that image. After feature extraction using LBP and spatial image processing, MLP as a classifier segments the pixels into vessels...
Image segmentation is an important process to extract information from complex medical images. Segmentation has wide application in medical field. The main objective of image segmentation is to partition an image into mutually exclusive and exhausted regions such that each region of interest is spatially contiguous and the pixels within the region are homogeneous with respect to a predefined criterion...
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