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Diabetic retinopathy (DR) is the damage to the eye's retina that occurs with long-term diabetes, which can eventually lead to blindness. Screening programs for DR are being introduced, however, an important prerequisite for automation is the accurate localization of the main anatomical features in the image, notably the optic disc (OD) and the macula. A series of interesting algorithms have been proposed...
In this paper, we propose a CAD (Computer aided diagnosis) system to analyze the RA (rheumatoid arthritis) and osteoporosis by using image processing techniques from the CR images. To analyze the RA, we develop a segmentation method for phalanges in CR Image by use of DCT (Discrete Cosine Transform) for detection of temporal change. The temporal change is detected using the difference image between...
Lesion segmentation is an important step in analysing dermoscopic skin lesion images. In this paper we achieve accurate lesion segmentation using a co-operative neural network-based edge detection approach coupled with a pre-processing step that enhances colour information and contrast of the images. Extensive experiments are carried out on a dataset of 100 dermoscopic images with known ground truths...
In this paper, the edge detection cellular neural network (CNN) has been applied to preprocess ultrasound B-Scan images of Chronic Hepatitis B(CHB) patients' livers. The preprocessed images are further converted via the wavelet transform. The ratio of the standard deviation of the coefficients of diagonal detail to the standard deviation of the preprocessed image seems to correlate with the degrees...
Early detection of medical abnormalities is an essential component in the accurate diagnosis and treatment of disease and disability. Automatically isolating the structure of the brain's ventricle system has the potential to assist neurologists in identifying abnormalities such as tumors, hydrocephalus and damage due to stroke. In this paper we present a multi-species genetic algorithm for isolating...
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