Publication: Automated Age-related Macular Degeneration screening system using fundus images
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Issued Date
2017
Resource Type
File Type
application/pdf
ISSN
1557170X
Other identifier(s)
2-s2.0-85032199228
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2017), p.1469-1472
Suggested Citation
Kunumpol P., Umpaipant W., Kanchanaranya N., Charoenpong T., Vongkittirux S., Kupakanjana T., Tantibundhit C. Automated Age-related Macular Degeneration screening system using fundus images. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. (2017), p.1469-1472. doi:10.1109/EMBC.2017.8037112 Retrieved from: https://hdl.handle.net/20.500.14740/4078
Abstract
This work proposed an automated screening system for Age-related Macular Degeneration (AMD), and distinguishing between wet or dry types of AMD using fundus images to assist ophthalmologists in eye disease screening and management. The algorithm employs contrast-limited adaptive histogram equalization (CLAHE) in image enhancement. Subsequently, discrete wavelet transform (DWT) and locality sensitivity discrimination analysis (LSDA) were used to extract features for a neural network model to classify the results. The results showed that the proposed algorithm was able to distinguish between normal eyes, dry AMD, or wet AMD with 98.63% sensitivity, 99.15% specificity, and 98.94% accuracy, suggesting promising potential as a medical support system for faster eye disease screening at lower costs. © 2017 IEEE.