Title :
Method of detecting kink-bearing vessels in a retinal fundus image
Author :
Wong, Damon W K ; Liu, Jiang ; Lim, Jiang Hwee ; Tan, Ngan Meng ; Zhang, Zhuo ; Li, Huiqi ; Lu, Shijian ; Wong, Tien Yin
Author_Institution :
Inst. for Infocomm Res., A*STAR, Singapore, Singapore
Abstract :
Glaucoma is the second leading cause of blindness worldwide. The risk of glaucoma can be determined by calculating the cup to disc ratio in retinal fundus images. To accurately detect the optic cup, kinks or bends in small and medium vessels are important indicators of the cup boundary. In this paper, we present a method of detecting such vessels, through the extraction of patches and generation of hybrid features in a SVM-based model. The segmentation results show good potential for the further development of this method.
Keywords :
biomedical imaging; blood vessels; diseases; eye; feature extraction; image classification; image segmentation; medical image processing; support vector machines; vision defects; wavelet transforms; SVM-based model; blindness; computer aided detection; cup boundary; glaucoma; kink-bearing vessel; optic cup; retinal fundus image; Blindness; Boring; Diseases; Image converters; Image edge detection; Image segmentation; Retina; Support vector machine classification; Support vector machines; Surfaces; SVM; computer aided detection; glaucoma; optic cup; vessels;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2010 the 5th IEEE Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4244-5045-9
Electronic_ISBN :
978-1-4244-5046-6
DOI :
10.1109/ICIEA.2010.5515225
