2017
DOI: 10.5120/ijca2017914130
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Automatic Detection of Glaucoma in Retinal Fundus Images through Image Processing and Data Mining Techniques

Abstract: Computational techniques are highly used in medical image analysis to aid the medical professionals. Glaucoma is a sight threatening retinal disease that needs attention at its early stages, though it does not reveal any symptoms. Glaucoma is identified usually through cup to disc ratio and ISNT rule. This work involves segmentation of blood vessels, segmentation of optic disc through proposed maximum voting of three segmentation algorithms (K-Means, Wavelet and Histogram based), segmentation of optic cup thro… Show more

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Cited by 8 publications
(4 citation statements)
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“…Therefore, the proportion of fat and other substances can be measured by the electrical resistance of the body [ 14 ]. In the 15-second kick measurement, the subject used the attacking leg as the upper kick and the other leg as the supporting leg in a badminton match [ 15 ]. The number of kicks in 15 seconds is measured and tested with two heads: the subject lies flat on the mat with the arms straight, the shoulder blades must touch the mat, the knees are straight, and the head and hands are raised simultaneously.…”
Section: Data Mining and Research Methodsmentioning
confidence: 99%
“…Therefore, the proportion of fat and other substances can be measured by the electrical resistance of the body [ 14 ]. In the 15-second kick measurement, the subject used the attacking leg as the upper kick and the other leg as the supporting leg in a badminton match [ 15 ]. The number of kicks in 15 seconds is measured and tested with two heads: the subject lies flat on the mat with the arms straight, the shoulder blades must touch the mat, the knees are straight, and the head and hands are raised simultaneously.…”
Section: Data Mining and Research Methodsmentioning
confidence: 99%
“…From the results, we can notice that the best performance to impulse noise is median filter and the best for Gaussian noise is an adaptive filter, but for retinal image without noise the (7) Gaussian filter is superior, to get more accurate results the performance of five filtering methods was tested using retinal images with different noises level (Tables 4 & 5). performance are compared to each other based on three parameters: mean squared error (mse), peak signal noise ratio (psnr) and structural similarity (ssim), our experiments have shown that the best performance founded for impulse noise is an adaptive median filter and for Gaussian noise is an adaptive filter.…”
Section: Resultsmentioning
confidence: 99%
“…There is a usable value, and the meaning that it cannot be divided again means that in the current branch, the feature has only a unique value. The characteristics such as the type and the size of the data volume select an appropriate algorithm to process the data [17]. As we all know, the ID3 algorithm is mainly for discrete variables.…”
Section: Decision Tree Algorithmmentioning
confidence: 99%