Learn More
Diabetic-related eye diseases are the most common cause of blindness in the world. So far the most effective treatment for these eye diseases is early detection through regular screenings. To lower the cost of such screenings, we employ state-of-the-art image processing techniques to automatically detect the presence of abnormalities in the retinal images(More)
Diabetic-related eye disease is the most common cause of blindness worldwide. The most effective treatment is early detection through regular screenings. This produces a large number of retinal photographs for the medical doctors to review. In our work, we employ a combination of innovative image processing and data mining techniques to automate the(More)
One of the greatest concern and immediate challenges to the current health care is the severe progression of diabetes. Diabetic retinopathy is an eye disease that associated with long-standing diabetes. The conventional method followed by ophthalmogists is the regular supervision of the retina. As this method takes time and energy of the ophthalmogists, a(More)
There is an increasing demand for systems that can automatically analyze images and extract semantically meaningful information. IRIS, an Integrated Retinal Information system, has been developed to provide medical professionals easy and unified access to the screening, trend and progression of diabetic-related eye diseases in a diabetic patient database.(More)
Different types of techniques are used to detect and segment the retinal diseases. Each technique gives a level of accuracy. Morphological methods have been extensively used in handling medical images. The goal of morphological operations is to remove imperfections by considering the structure of the image. This paper proposes an automated method to detect,(More)
  • 1