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Classification of pathology in diabetic eye disease

Abstract
Proliferative diabetic retinopathy is a complication of diabetes that can eventually lead to blindness. Early identification of this complication reduces the risk of blindness by initiating timely treatment. We report the utility of pattern analysis tools linked with a simple linear discriminant analysis that not only identifies new vessel growth in the retinal fundus but also localises the area of pathology. Ten fluorescein images were analysed using seven feature descriptors including area, perimeter, circularity, curvature, entropy, wavelet second moment and the correlation dimension. Our results indicate that traditional features such as area or perimeter measures of neovascularisation associated with proliferative retinopathy were not sensitive enough to detect early proliferative retinopathy (SNR = 0.76, 0.75 respectively). The wavelet second moment provided the best discrimination with a SNR of 1.17. Combining second moment, curvature and global correlation dimension provided a 100% discrimination (SNR = 1).
Type
Conference Contribution
Type of thesis
Series
Citation
Jelinek, H. F., Leandro, J., Cesar, R. M. & Cree, M. J. (2005). Classification of pathology in diabetic eye disease. In B. C. Lovell & A. J. Maeder(eds), WDIC 2005, APRS Workshop on digital image computing, The University of Queensland, Brisbane, Australia, 21 February, 2005(pp. 9-13).
Date
2005
Publisher
The University of Queensland
Degree
Supervisors
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