Classification of Gastric Tumors using Shape Features of Gland

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Recently in Japan, pathologists have been in short supply, while each pathological diagnosis requires a substantial amount of time because each analyte must be inspected by multiple pathologists for adequate diagnosis. This paper deals with the classification method of gastric cancer and gastric adenoma, using image processing and pattern analysis. We first select the R component and G component from the RGB basis of the digital image, and the Y component from the YIQ basis for our system. After pre-processing, we automatically extracted the shape of the nucleus and cytoplasm. After many inspections, we selected 40 features for shape of the nucleus and cytoplasm and 14 features for texture within the cytoplasm for assessment of tumors. Principal component analysis, F test of homoscedasticity, t test of difference of average, stepwise method for selecting the smaller number of features, and discriminant method using Mahalanobis distance were all performed. Total ratio of diagnosis reached 96.9%, showing the validity of our proposed method.

収録刊行物

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society  

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 126(10), 1242-1248, 2006-10-01 

    The Institute of Electrical Engineers of Japan

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被引用文献:  1件

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各種コード

  • NII論文ID(NAID)
    10018780721
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    ENG
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    8526294
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
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