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Image Classification for Age-related Macular Degeneration Screening using Hierarchical Image Decompositions and Graph Mining
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BibTeX
@MISC{Hanafi_imageclassification,
author = {Mohd Hanafi and Ahmad Hijazi and Chuntao Jiang and Frans Coenen},
title = {Image Classification for Age-related Macular Degeneration Screening using Hierarchical Image Decompositions and Graph Mining},
year = {}
}
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Abstract
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.
Keyphrases
graph mining hierarchical image decomposition age-related macular degeneration screening image classification classification technique angular partitioning new image mining technique weighted frequent sub-tree mining algorithm age-related macular degeneration adult blindness automated detection tree structure common cause developed world identified sub-graphs colour fundus photograph feature vector representation novel hierarchical image decomposition mechanism
