Glomeruli segmentation based on neural network with fault tolerance analysis

研究成果: Conference contribution

1 引用 (Scopus)

抄録

Image segmentation, which is the first essential and fundamental issue in the image analysis and pattern recognition, is a classical difficult problem in image processing. In the computer-aided diagnosis system of the renal biopsy images in microscope, the correct segmentation of glomerulus is an important step for automatic analysis. Complex characteristics of renal biopsy images lead to the difficulty in boundary features description. A kind of feature operator based on the definition of the cavum boundary is proposed in this paper. According to this operator, a nonlinear thresholding surface can be constructed by neural network, and the appropriate surface can be selected to enhance the cavum boundary by the fault tolerance analysis. After denoising, the segmentation results can be obtained. Experimental results indicate that this method can enhance the boundary and suppress noises at the same time; it can obtain good segmented results and has a fine adaptability to various sample images.

元の言語English
ホスト出版物のタイトルProceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008
ページ401-404
ページ数4
1
DOI
出版物ステータスPublished - 2008
イベント2008 International Symposium on Computational Intelligence and Design, ISCID 2008 - Wuhan
継続期間: 2008 10 172008 10 17

Other

Other2008 International Symposium on Computational Intelligence and Design, ISCID 2008
Wuhan
期間08/10/1708/10/17

Fingerprint

Biopsy
Fault tolerance
Neural networks
Computer aided diagnosis
Image segmentation
Image analysis
Pattern recognition
Image processing
Microscopes

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture

これを引用

Zhang, J., & Furuzuki, T. (2008). Glomeruli segmentation based on neural network with fault tolerance analysis. : Proceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008 (巻 1, pp. 401-404). [4725636] https://doi.org/10.1109/ISCID.2008.222

Glomeruli segmentation based on neural network with fault tolerance analysis. / Zhang, Jun; Furuzuki, Takayuki.

Proceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008. 巻 1 2008. p. 401-404 4725636.

研究成果: Conference contribution

Zhang, J & Furuzuki, T 2008, Glomeruli segmentation based on neural network with fault tolerance analysis. : Proceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008. 巻. 1, 4725636, pp. 401-404, 2008 International Symposium on Computational Intelligence and Design, ISCID 2008, Wuhan, 08/10/17. https://doi.org/10.1109/ISCID.2008.222
Zhang J, Furuzuki T. Glomeruli segmentation based on neural network with fault tolerance analysis. : Proceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008. 巻 1. 2008. p. 401-404. 4725636 https://doi.org/10.1109/ISCID.2008.222
Zhang, Jun ; Furuzuki, Takayuki. / Glomeruli segmentation based on neural network with fault tolerance analysis. Proceedings of the 2008 International Symposium on Computational Intelligence and Design, ISCID 2008. 巻 1 2008. pp. 401-404
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