Image classification for age-related macular degeneration screening using hierarchical image decompositions and graph mining

Mohd Hanafi Ahmad Hijazi, and Jiang, Chuntao and Coenen, Frans P. and Zheng, Yalin (2011) Image classification for age-related macular degeneration screening using hierarchical image decompositions and graph mining. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2011, 5-9 September 2011, Athens, Greece.

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Official URL: http://dx.doi.org/10.1007/978-3-642-23783-6_5

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.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Hierarchical image decomposition, Image classification, Image partitioning, Weighted graph mining, Age-related macular degeneration, Angular partitioning, Automated detection, Classification technique, Feature vectors, Fundus photographs, Graph mining, Image decomposition, Image mining, Image partitioning, Mining algorithms, Subgraphs, Tree structures, Weighted graph, Image analysis, Image classification, Learning systems, Ophthalmology, Photography, Plant extracts, Trees (mathematics)
Subjects:?? QA75.5-76.95 ??
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:4948
Deposited By:IR Admin
Deposited On:25 Sep 2012 17:44
Last Modified:25 Sep 2012 17:44

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