Abstract
Age-related Macular Degeneration (AMD) is the most common cause of adult blindness in the developed world. This paper describes a new image mining technique to perform automated detection of AMD from colour fundus photographs. The technique comprises a novel hierarchical image decomposition mechanism founded on a circular and angular partitioning. The resulting decomposition is then stored in a tree structure to which a weighted frequent sub-tree mining algorithm is applied. The identified sub-graphs are then incorporated into a feature vector representation (one vector per image) to which classification techniques can be applied. The results show that the proposed approach performs both efficiently and accurately. © 2011 Springer-Verlag.
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Hijazi, M. H. A., Jiang, C., Coenen, F., & Zheng, Y. (2011). Image classification for age-related macular degeneration screening using hierarchical image decompositions and graph mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6912 LNAI, pp. 65–80). Springer Verlag. https://doi.org/10.1007/978-3-642-23783-6_5
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