Multifractal feature based cancer detection for pathological images

Chamidu Atupelage, Hiroshi Nagahashi, Michiie Sakamoto, Masahiro Yamaguchi, Akinori Hashiguchi

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

This paper presents a significant multifractal feature description based texture discriminating technique to examine the cancer and non-cancer regions in pathological images. We acquired the characteristics (local singularity and global regularity information) of the texture using multifractal computation and used them to discriminate the highly complex visual patterns shown in the pathological images. The proposed feature description method was applied two different samples of pathological cancer liver images in different magnifications (given by digital slider) with different patch sizes (patch is a local window that we used to capture the data for training and testing). The outcomes of the experiments indicate that the proposed multifractal feature description based texture classification method is remarkable.

本文言語English
ホスト出版物のタイトル5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011
DOI
出版ステータスPublished - 2011 7 14
イベント5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011 - Wuhan, China
継続期間: 2011 5 102011 5 12

出版物シリーズ

名前5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011

Other

Other5th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2011
CountryChina
CityWuhan
Period11/5/1011/5/12

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

フィンガープリント 「Multifractal feature based cancer detection for pathological images」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル