Random Forestを用いた白血球分画の自動分類システムの開発
Random Forestを用いた白血球分画の自動分類システムの開発
カテゴリ: 論文誌(論文単位)
グループ名: 【C】電子・情報・システム部門
発行日: 2018/04/01
タイトル(英語): Development of Automatic Classification System for Leukocyte Images Using Random Forest
著者名: 富山 眞之介(東京理科大学大学院 基礎工学研究科 電子応用工学専攻),坂田(柳元) 麻実子(筑波大学 医学医療系),千葉 滋(筑波大学 医学医療系),相川 直幸(東京理科大学)
著者名(英語): Shinnosuke Tomiyama (Tokyo University of Science), Mamiko Sakata-Yanagimoto (University of Tsukuba Faculty of Medicine), Shigeru Chiba (University of Tsukuba Faculty of Medicine), Naoyuki Aikawa (Tokyo University of Science)
キーワード: 末梢血液像,グラムシュミッドの正規直交化法,ランダムフォレスト blood figure analysis of peripheral blood,GramSchmidt orthonormalization,Random Forest
要約(英語): Classifying leukocyte and examining their proportions is a very important for disease examination and diagnosis. This examination needs the knowledge of experts and a lot of time. Therefore, many automatic leukocyte images classification algorithms have been proposed. There is a method to classify 13 types blood cells using 1 vs 1 Support Vector Machine(SVM) in one of them. In the conventional method, leukocyte images are classified with the 26-dimensional feature vectors. However, the classification accuracy, is poor with these feature vectors in granulocytes in this method. In this paper, we propose new feature vectors to improve the classification accuracy of blast cells with low classification accuracy among the leukocyte fractions. That is, we add two feature vectors in the proposed method. And we improve the accuracy of the whole by using a random forest for the classifier.
本誌: 電気学会論文誌C(電子・情報・システム部門誌) Vol.138 No.4 (2018) 特集:信号処理と制御の融合に基づく新領域の創出
本誌掲載ページ: 347-351 p
原稿種別: 論文/日本語
電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/138/4/138_347/_article/-char/ja/
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