Multimodal method for cell membrane extraction in hepatic histological images

Nobumitsu Matsushita, Masanobu Takahashi, Masayuki Nakano

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

A multimodal method, which uses different kinds of imaging methods, was applied to extract cell membranes in microscopic images of hematoxylin and eosin-stained hepatic histological sections. Cell membrane extraction in hepatic histological images is difficult because the color difference between the cell membrane and the cytoplasm is small in bright-field images. Three kinds of imaging methods, bright-field, dark-field, and phase-contrast imaging, were used because they are readily available for general pathologists. These imaging methods can be switched easily by revolving a combined condenser with the same phase-contrast objective lens. Therefore, little additional time and cost are needed for this approach. Experimental results show the effectiveness of this approach. The correct rate was improved by using additional color information obtained by dark-field and phase-contrast images compared to conventional bright-field images. The best correct rate was obtained when color information of all three images was used. A graphical user interface to calculate the N/C ratio was developed by combining cell membrane extraction with conventional cell nucleus extraction.

本文言語English
ホスト出版物のタイトル2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
ページ4068-4071
ページ数4
DOI
出版ステータスPublished - 2010 12月 1
イベント2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
継続期間: 2010 8月 312010 9月 4

出版物シリーズ

名前2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Conference

Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
国/地域Argentina
CityBuenos Aires
Period10/8/3110/9/4

ASJC Scopus subject areas

  • 生体医工学
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • 健康情報学

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