Title :
A model-based approach for automated feature extraction in fundus images
Author :
Li, Huiqi ; Chutatape, Opas
Author_Institution :
Sch. of Comput., Nat. Univ. of Singapore, Singapore
Abstract :
A new approach to automatically extract the main features in color fundus images is proposed. The optic disk is localized by principal component analysis (PCA) and its shape is detected by a modified active shape model (ASM). Exudates are extracted by the combined region growing and edge detection. A fundus coordinate system is further set up based on fovea localization to provide a better description of the features in fundus images. The success rates achieved are 99%, 94%, and 100% for disk localization, disk boundary detection, and fovea localization respectively. The sensitivity and specificity for exudate detection are 100% and 71%. The success of the proposed algorithms can be attributed to utilization of the model-based methods.
Keywords :
biomedical optical imaging; edge detection; feature extraction; image colour analysis; medical image processing; principal component analysis; PCA; active shape model; color fundus images; disk boundary detection; edge detection; exudate detection; eye diseases; model-based feature extraction; optic disk localization; principal component analysis; Active shape model; Biomedical imaging; Blood vessels; Feature extraction; Geometrical optics; Image edge detection; Lesions; Optical devices; Optical sensors; Principal component analysis;
Conference_Titel :
Computer Vision, 2003. Proceedings. Ninth IEEE International Conference on
Conference_Location :
Nice, France
Print_ISBN :
0-7695-1950-4
DOI :
10.1109/ICCV.2003.1238371
