ACADSTAFF UGM
| Judul/Title | Analysis of Texture-based Features for Image Classification of Retinal Exudates |
| Penulis/Author | Prof. Ir. Hanung Adi Nugroho, S.T., M.Eng., Ph.D., IPM., SMIEEE. (1) ; WIDHIA OKTOEBERZA KZ (2); Ratna Lestari Budiani Buana (3); Teguh Bharata Adji, S.T., M.T., M.Eng., Ph.D (4) |
| Tanggal/Date | 2017 |
| Kata Kunci/Keyword | |
| Abstrak/Abstract | Diabetic retinopathy is one of the primary causes of blindness as complication of long term diabetes. The permanent vision loss can be avoided by conducting early detection of retinopathy symptoms such as retinal exudates. This paper proposes a scheme to classify fundus images whether containing exudates based on analysis of extracted texture features. Removal of optic disc and detection of exudate candidate area were firstly conducted. Afterwards, some texture features consisting of five features of grey level co-occurrence matrices (GLCM), eleven features of grey level of run-length matrices (GLRLM) and six histogram-based features were extracted from candidate exudates detected. These extracted features subsequently underwent classification process by using multi-layer perceptron (MLP) classifier. The performance of proposed scheme was evaluated on 80 fundus images taken from DIARETDB1 comprising of 38 images with exudates and 42 images without exudates. The best evaluation result of classification was achieved by using five GLCM features with 95% of accuracy, 97.37% of sensitivity and 92.86% of specificity. These results indicate that the proposed scheme successfully detects exudates and also classifies fundus images either containing exudates or no exudates. In addition, the implementation of the proposed scheme is expected to assist the ophthalmologists in monitoring and diagnosing diabetic retinopathy especially on the presence of retinal exudates. Analysis of Texture-based Features for Image Classification of Retinal Exudates. |
| Level | Internasional |
| Status |