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- Title
Data Mining for AMD Screening: A Classification Based Approach.
- Authors
Mohd Hanafi Ahmad Hijazi; Coenen, Frans; Yalin Zheng
- Abstract
This paper investigates the use of three alternative approaches to classifying retinal images. The novelty of these approaches is that they are not founded on individual lesion segmentation for feature generation, instead use encodings focused on the entire image. Three different mechanisms for encoding retinal image data were considered: (i) time series, (ii) tabular and (iii) tree based representations. For the evaluation two publically available, retinal fundus image data sets were used. The evaluation was conducted in the context of Age-related Macular Degeneration (AMD) screening and according to statistical significance tests. Excellent results were produced: Sensitivity, specificity and accuracy rates of 99% and over were recorded, while the tree based approach has the best performance with a sensitivity of 99.5%. Further evaluation indicated that the results were statistically significant. The excellent results indicated that these classification systems are ideally suited to large scale AMD screening processes.
- Subjects
DATA mining; RETINAL degeneration; RETINAL imaging; IMAGE segmentation; TIME series analysis
- Publication
International Journal of Simulation: Systems, Science & Technology, 2014, Vol 15, Issue 2, p57
- ISSN
1473-8031
- Publication type
Article
- DOI
10.5013/IJSSST.a.15.02.09