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In this paper, a robust and efficient histogram based template matching method for automatic detection of Optic Disc (OD) in retinal images to help ophthalmologists for diagnosis of retinal diseases is presented. Based on camera field of view (FOV) and image resolution, the OD size estimation algorithm for creation of specific size templates is proposed. Color plane histograms of OD region were used...
Segmentation of optic disk (OD) is a very important step in automatic Diabetic Retinopathy screening. In this paper, we presented a robust and novel template matching algorithm for automatic detection of OD in retinal images. The size of OD area depends on camera field of view and image resolution. Based on these criteria we formulated and presented OD size estimation algorithm and it is used to create...
In 2015, according to the International Diabetes Federation (IDF), around 415 million of people worldwide lived with diabetes and it was predicted to be increased by 642 million of people in 2040. One of the diabetes complications that affect the retina is known as diabetic retinopathy (DR). It is indicated by the presence of hard exudates as the main pathology of DR. In retinal fundus images, hard...
Exudates are one of the abnormalities present on the retina which are used for identification of diseases like Diabetic Retinopathy and Macular Edema. There arises a need for automated and correct segmentation of exudates from digital fundus images. This paper proposes an automated computer vision technique for efficient exudates segmentation from fundus images. The proposed method segments the exudates...
Glaucoma and Diabetic Retinopathy are the leading common cause of vision loss. Optic Disc and macula are the important landmark for the detection of these retinal pathology. Even though, the manual screening of Optic Disc and macula are available, they consume more time and have more human error. Therefore, there is a need of an automated application for the reliable and efficient localization of...
This paper proposes a method to detect optic disk (OD) automatically in fundus image of retina without using background mask and blood vessels. Based on the properties of OD, an idea of curve operator is presented here. This method has been implemented on three public databases and the promising results are obtained. The experimental results indicate that this proposed method of automatic OD detection...
Automatic feature detection in retinal fundus images is a fundamental issue to diagnosis eye diseases such as Glaucoma. For example, Optic Disc (OD) is a main feature for diagnosing retinal fundus diseases such as Glaucoma. This paper presents a novel algorithm for OD detection in retinal fundus images based on region growing. Image thresholding based on the entropy of the input image histogram and...
Exudates and drusens detection and measurement from the retina background makes a significant impact on the diagnosis of retinal pathologies. These diseases usually appear as cotton wall spots, yellowish exudates and drusens (macula degeneration). Information about illness severity can be inferred by the measurement of the sizes of the exudates and drusens and comparing them to the retina background...
This paper proposes an image processing technique for the detection of glaucoma which mainly affects the optic disc by increasing the cup size. During early stages it was difficult to detect Glaucoma, which is in fact second leading cause of blindness. In this paper glaucoma is categorized through extraction of features from retinal fundus images. The features include (i) Cup to Disc Ratio (CDR),...
The optic disc (OD) and exudates form the main features of fundus images for diagnosing eye disease such as diabetic retinopathy and glaucoma. In this paper, an algorithm for the extraction of OD and exudates from fundus images based on marker controlled watershed segmentation is presented. The proposed algorithm makes use of average filtering and contrast adjustment as preprocessing steps before...
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