Multifractal computation for nuclear classification and hepatocellular carcinoma grading

Chamidu Atupelage, Hiroshi Nagahashi, Masahiro Yamaguchi, Fumikazu Kimura, Tokiya Abe, Akinori Hashiguchi, Michiie Sakamoto

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Hepatocellular carcinoma (HCC) is graded mainly based on the characteristics of liver cell nuclei. This paper proposes a textural feature descriptor and a novel computational method for classifying liver cell nuclei and grading the HCC histological images. The proposed textural feature descriptor observes local and spatial characteristics of the texture patterns by using multifractal computation. The textural features are utilized for nuclear segmentation, fiber region detection, and liver cell nuclei classification. Four categories of nuclear features are computed such as texture, geometry, spatial distribution, and surrounding texture, for HCC classification. Significance of liver cell nuclei classification method is evaluated by classifying non-neoplastic and tumor tissues. Furthermore, characteristics of the liver cell nuclei were utilized for grading a set of HCC images into four classes and obtained 97.77% classification accuracy.

本文言語English
ホスト出版物のタイトルProceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013
ページ415-420
ページ数6
DOI
出版ステータスPublished - 2013
イベント10th IASTED International Conference on Biomedical Engineering, BioMed 2013 - Innsbruck, Austria
継続期間: 2013 2 132013 2 15

出版物シリーズ

名前Proceedings of the IASTED International Conference on Biomedical Engineering, BioMed 2013

Other

Other10th IASTED International Conference on Biomedical Engineering, BioMed 2013
CountryAustria
CityInnsbruck
Period13/2/1313/2/15

ASJC Scopus subject areas

  • Biomedical Engineering

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