Data mining techniques for the screening of age-related macular degeneration

Mohd Hanafi Ahmad Hijazi and Coenen, Frans P. and Zheng, Yalin (2012) Data mining techniques for the screening of age-related macular degeneration. Knowledge-Based Systems, 29. pp. 83-92. ISSN 0950-7051


Download (43kB) | Preview


Age related macular degeneration (AMD) is the primary cause of adult blindness. Currently AMD cannot be cured, however early detection does allow the progress of the condition to be inhibited. One of the first symptoms of AMD is the presence of fatty deposits, called drusen, on the retina. The presence of drusen may be identified through the manual inspection/screening of retinal images. This task, however, requires recourse to domain experts and is therefore resource intensive. This paper proposes and compares two data mining techniques to support the automated screening for AMD. The first uses spatial-histograms, that maintain both image colour and spatial information, for the image representation; to which a case based reasoning (CBR) classification technique is applied. The second is founded on a hierarchical decomposition of the image set so that a tree representation is generated. A weighted frequent sub-graph mining technique is then applied to this representation to identify sub-trees that frequently occur across the data set. The identified sub-trees are then encoded in the form of feature vectors to which standard classification techniques can be applied.

Item Type: Article
Keyword: Case based reasoning, Image classification, Image decomposition, Spatial-histograms, Weighted frequent sub-graph mining
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1-2040 Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Department: SCHOOL > School of Engineering and Information Technology
Depositing User: ADMIN ADMIN
Date Deposited: 05 Apr 2012 17:05
Last Modified: 17 Oct 2017 11:42

Actions (login required)

View Item View Item