An Automatic Diabetic Retinopathy Detection Using Artificial Neural Network
| dc.contributor.advisor | Getachew, Alemu (PhD) | |
| dc.contributor.author | Senait, Getahun | |
| dc.date.accessioned | 2018-09-24T06:05:27Z | |
| dc.date.accessioned | 2023-11-04T15:14:39Z | |
| dc.date.available | 2018-09-24T06:05:27Z | |
| dc.date.available | 2023-11-04T15:14:39Z | |
| dc.date.issued | 2018-05 | |
| dc.description.abstract | Diabetic retinopathy is a disease that affects the eye of a diabetic patient. Diabetics being the abnormal level of glucose in the human blood, it is a cause for several types of organ disorders in the body. One of them being the eye. Diabetic retinopathy is caused when the blood vessels in the eye start liking blood in to the surface of the eye. Detection of diabetic retinopathy at different stages of the disease is an invaluable input for physicians in the medical field. In this papera research has been made for detection of diabetic retinopathy exudates by using an artificial neural network. The process of image detection starts from image preprocessing, next is image segmentation then feature selection and finally classification. In the image pre-processing a median filtering and adaptive histogram equalization is used. The image blood vessels and Optic disk are then segmented out using morphological analysis. Accuracy of segmentation of the optic disk is 90%, 87% and 90 % for exudates containing images, normal images and all images that contain all features of diabetic retinopathy respectively. The gray level co-occurrencematrix of the image is then calculated to evaluate the textual features. Fourteen features are then used to feed the artificial neural network. Two fundus image data sets(STARE 402 images, and DIABETRETDB1 with 130 images) were obtained from two medical universities have been used for the detection process. Using the proposed methodology, a detection performance of 84% sensitivity and 63% specificity is obtained.The implementation is done by using mathlab 2015. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/12137 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | AAU | en_US |
| dc.subject | Diabetic Retinopathy Detection | en_US |
| dc.subject | Artificial Neural Network | en_US |
| dc.title | An Automatic Diabetic Retinopathy Detection Using Artificial Neural Network | en_US |
| dc.type | Thesis | en_US |