Please use this identifier to cite or link to this item: https://doi.org/10.1109/TBME.2003.820400
Title: Automated Feature Extraction in Color Retinal Images by a Model Based Approach
Authors: Li, H. 
Chutatape, O.
Keywords: ASM
Biomedical image processing
Exudate
Feature extraction
Fovea
Optic disk
PCA
Retinal image
Issue Date: 2004
Source: Li, H., Chutatape, O. (2004). Automated Feature Extraction in Color Retinal Images by a Model Based Approach. IEEE Transactions on Biomedical Engineering 51 (2) : 246-254. ScholarBank@NUS Repository. https://doi.org/10.1109/TBME.2003.820400
Abstract: Color retinal photography is an important tool to detect the evidence of various eye diseases. Novel methods to extract the main features in color retinal images have been developed in this paper. Principal component analysis is employed to locate optic disk; A modified active shape model is proposed in the shape detection of optic disk; A fundus coordinate system is established to provide a better description of the features in the retinal images; An approach to detect exudates by the combined region growing and edge detection is proposed. The success rates of disk localization, disk boundary detection, and fovea localization are 99%, 94%, and 100%, respectively. The sensitivity and specificity of exudate detection are 100% and 71%, correspondingly. The success of the proposed algorithms can be attributed to the utilization of the model-based methods. The detection and analysis could be applied to automatic mass screening and diagnosis of the retinal diseases.
Source Title: IEEE Transactions on Biomedical Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/39339
ISSN: 00189294
DOI: 10.1109/TBME.2003.820400
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

340
checked on Dec 11, 2017

WEB OF SCIENCETM
Citations

237
checked on Dec 11, 2017

Page view(s)

51
checked on Dec 9, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.