The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Diabetic macular edema (DME) is a common vision threatening complication of diabetic retinopathy which can be assessed by detecting exudates (a type of bright lesion) in fundus images. In this work, two new methods for the detection of exudates are presented which do not use a supervised learning step; therefore, they do not require labelled lesion training sets which are time consuming to create,...
Vessel segmentation is very important in an automatic screening system for fundus images. Vessels are often segmented and removed from retinal images before the other residual lesions are detected. Incomplete vessel removal usually causes a false positive in lesion detection, especially for Microaneurysms detection. Segmenting vessels in spatial image domain makes miss detection due to non illumination...
In this paper, we propose an effective framework to automatically segment hard exudates (HEs) in fundus images. Our framework is based on a coarse-to-fine strategy, as we first get a coarse result allowed of some negative samples, then eliminate the negative samples step by step. In our framework, we make the most of the multi-channel information by employing a boosted soft segmentation algorithm...
The proper segmentation of the vascular system of the retina has a very important role in automatic screening systems. Its detection helps the localization of other anatomical parts and also the detection of possible vascular disorders. State-of-the-art machine learning algorithms are reported to have good performance in this field. However, with the spatial resolution of the fundus images growing,...
Characteristic of retinal vasculature has been an important indicator for many diseases such as hypertension and diabetes. A digital image analysis system can assist medical experts to make accurate diagnosis in an efficient manner. This paper presents the computer based approach to the automated segmentation of blood vessels in retinal images. The detection of the retinal vessel is achieved by performing...
Analyzing retinal fundus image is important for early detection of diseases related to the eye. However, in fundus images the contrast between retinal blood vessels and the background is very low. Hence, analyzing or visualizing tiny blood vessels is difficult. Fluorescein angiogram overcomes this imaging problem but it is an invasive procedure that leads to other physiological problems. In this work,...
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...
Diabetic Retinopathy (DR) is a common cause of visual impairment among people of working age in industrialized countries. Automatic recognition of DR lesions, like hard exudates (HEs), in fundus images can contribute to the diagnosis and screening of this disease. In this study, we extracted a set of features from image regions and selected the subset which best discriminates between HEs and the retinal...
Due to its blood microcirculation, the retina is one of the first organs affected by hypertension and diabetes: retinal damages can lead to serious visual loss, that can be avoided by an early diagnosis. The most distinctive sign of diabetic retinopathy or severe hypertensive retinopathy are dark lesions such as haemorrhages and microaneurysms (HM), and bright lesions such as hard exudates (HE) and...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.