Glomerulus extraction by using genetic algorithm for edge patching

Authors:
Jiaxin Ma;Jun Zhang;Jinglu Hu
Affiliations:
Graduate School of Information, Production and Systems, Waseda University, Kitakyshu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyshu, Fukuoka, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyshu, Fukuoka, Japan
Venue:
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Year:
2009

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Abstract

Glomerulus is the filtering unit of the kidney. In the computer aided diagnosis system designed for kidney disease, glomerulus extraction is an important step for analyzing kidney-tissue image. Against the disadvantages of traditional methods, this paper proposes a glomerulus extraction method using genetic algorithm for edge patching. Firstly, Canny edge detector is applied to get discontinuous edges of glomerulus. After labeling to remove the noises, genetic algorithm is used to search for optimal patching segments to join those edges together. Lastly, the edges and the patching segments with high fitness would be able to form the whole edge of the glomerulus. Experiments and comparisons indicate the proposed method can extract the glomerulus from kidney-tissue image both fast and accurately.