Classification of gastric tumors on gastric biopsy images

Ryo Ohtsuki, Toshiyuki Tanaka

研究成果: Paper査読

抄録

The well-known Group Classification method for hematoxylin and eojin stained gastric tumors uses morphological features of histology patterns within a tissue slide to classify it into 5 grades from Group1 to Group5. Our approach developed an automated classification method being used for automated Group Classification of gastric tumor images. We have demonstrate the performance of the proposed method for a three class classification ± Group1 (benign), Group3 (gastric adenoma), Group5 (gastric cancer) ± on a 90 teaching dataset and 90 test dataset using Support Vector Machine and achieved accuracy of 75.6% on Group1, 64.4% on Group3, and 95.6% on Group5. Our approach combines the morphological features such as nuclear-cytoplasmic ratio, some texture features, and HLAC (higher order local autocorrelation).

本文言語English
ページ2502-2506
ページ数5
出版ステータスPublished - 2013
イベント2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013 - Nagoya, Japan
継続期間: 2013 9月 142013 9月 17

Other

Other2013 52nd Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2013
国/地域Japan
CityNagoya
Period13/9/1413/9/17

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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