Title :
Effective Detection of Retinal Exudates in Fundus Images
Author :
Wang, Huan ; Hsu, Wynne ; Lee Mong Li
Author_Institution :
Coll. of Inf. Sci. & Eng., Ningbo Univ., Ningbo, China
Abstract :
Diabetic-related eye diseases are the most common cause of blindness in the world. Early detection through regular screenings is the most effective treatment for these eye diseases. To improve the efficiency of such screenings, it is very important that effectively finding the presence of abnormalities in the retinal images captured during the screenings. In this paper, it is focused on automatically detecting one of the abnormal signs: the presence of´ exudates/lesions in the retinal images. A novel approach that combines median filtering and dynamic clustering analysis is proposed. Experimental results indicate that the new algorithm is easier, faster and more effective for lesion detection from retinal images of various qualities.
Keywords :
diseases; eye; filtering theory; image colour analysis; median filters; medical image processing; pattern clustering; statistical analysis; MDD classifier; color information; dynamic clustering analysis; eye diseases; fundus images; lesion detection; median filtering; minimum distance discriminant; retinal exudates; retinal images; statistical classification; Algorithm design and analysis; Blindness; Clustering algorithms; Diabetes; Diseases; Filtering; Image analysis; Image color analysis; Lesions; Retina;
Conference_Titel :
Biomedical Engineering and Informatics, 2009. BMEI '09. 2nd International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-4132-7
Electronic_ISBN :
978-1-4244-4134-1
DOI :
10.1109/BMEI.2009.5305381