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In the framework of computer assisted diagnosis of diabetic retinopathy, a new algorithm for detection of exudates is presented and discussed. The presence of exudates within the macular region is a main hallmark of diabetic macular edema and allows its detection with a high sensitivity. Hence, detection of exudates is an important diagnostic task, in which(More)
This paper presents an algorithm based on mathematical morphology and curvature evaluation for the detection of vessel-like patterns in a noisy environment. Such patterns are very common in medical images. Vessel detection is interesting for the computation of parameters related to blood flow. Its tree-like geometry makes it a usable feature for(More)
Image registration is a real challenge because physicians handle many images. Temporal registration is necessary in order to follow the various steps of a disease, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for(More)
PURPOSE We present the development of a tool for the automatic detection of microaneurysms and its clinical evaluation. The intention of this tool is to facilitate the diagnosis of diabetic retinopathy in general screening programs. METHOD The designed and developed tool consists of three stages of processing: 1) Obtaining of the basic image of eye with(More)
At present, Diabetic Retinopathy was considered as the main cause of blindness for diabetic patients. The Diabetic Retinopathy can be identified at an earlier stage by detecting the microaneurysms in the retina of the patients. For this purpose, opthalmologists will regularly supervise the retinal images obtained using the color fundus camera. During this(More)
This paper presents new algorithms based on mathematical morphology for the detection of the optic disc and the vascular tree in noisy low contrast color fundus photographs. Both features – vessels and optic disc – deliver landmarks for image registration and are indispensable to the understanding of retinal fundus images. For the detection of the optic(More)
Diabetic retinopathy (DR) is an eye disease caused by the complication of diabetes and we should detect it early for effective treatment. As diabetes progresses, the vision of a patient may start deteriorate and lead to diabetic retinopathy. As a result, two groups were identified, namely non-proliferative diabetic retinopathy (NPDR) and proliferative(More)
Fundus AutoFluorescence (FAF) images are widely used in the diagnosis and follow-up of Age-related Macular Degeneration, which is the leading cause of blindness in people over 55. There are two kinds of AMD: wet and dry. The most common is the dry form. It is characterized by atrophies of the the retinal pigment epithelium (RPE) with subsequent(More)
The wavelet transform decomposes a given signal into a time-frequency representation, preserving the locality of both. Given that the local relief elevation is correlated to the phase difference in the stereo pair of images, we demonstrate a frequency selective relief reconstruction from a stereo pair of images, utilizing the dual-tree complex wavelet(More)