Contour extraction of glomeruli by using genetic algorithm for edge patching

Jun Zhang, Takayuki Furuzuki, Hong Zhu

研究成果: Article

6 引用 (Scopus)

抄録

Glomeruli extraction is a vital step in computer-aided diagnosis systems of kidney disease. Since there are not only glomeruli but also other tissues in an image, when detecting the edges of glomeruli, lot of noises caused by other tissues will be detected at the same time. These noises cause discontinuous edges of glomeruli when some operation, such as labeling, is applied to denoise. According to this characteristic, this article proposes a contour extraction method based on genetic algorithm (GA) for edge patching. First, a Canny operator is applied to obtain the edges of glomeruli with noises. Then labeling and other operations such as dilation, thinning and cross-point deletion are applied to markedly remove the noises. After the above operations, GA is finally used to search for optimal patching segments to join the discontinuous edges together and a closed curve with highest fitness would be able to form the contour of glomeruli. Experimental results show that the proposed method performs well for the renal biopsy images.

元の言語English
ページ(範囲)229-235
ページ数7
ジャーナルIEEJ Transactions on Electrical and Electronic Engineering
6
発行部数3
DOI
出版物ステータスPublished - 2011 5

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Labeling
Genetic algorithms
Tissue
Computer aided diagnosis
Biopsy

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

これを引用

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AB - Glomeruli extraction is a vital step in computer-aided diagnosis systems of kidney disease. Since there are not only glomeruli but also other tissues in an image, when detecting the edges of glomeruli, lot of noises caused by other tissues will be detected at the same time. These noises cause discontinuous edges of glomeruli when some operation, such as labeling, is applied to denoise. According to this characteristic, this article proposes a contour extraction method based on genetic algorithm (GA) for edge patching. First, a Canny operator is applied to obtain the edges of glomeruli with noises. Then labeling and other operations such as dilation, thinning and cross-point deletion are applied to markedly remove the noises. After the above operations, GA is finally used to search for optimal patching segments to join the discontinuous edges together and a closed curve with highest fitness would be able to form the contour of glomeruli. Experimental results show that the proposed method performs well for the renal biopsy images.

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