文脈情報を用いた教師付データが少ない場合に有効な細胞内画像からの輝点検出

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: 2014/11/01

タイトル(英語): Effective Light Spot Detection in Intracellular Images for Small Number of Supervised Data Using Contextual Information

著者名: 丹羽　貴也（名城大学大学院理工学研究科），堀田　一弘（名城大学大学院理工学研究科）

著者名(英語): Takaya Niwa (Graduate School of Science and Technology, Meijo University), Kazuhiro Hotta (Graduate School of Science and Technology, Meijo University)

キーワード: 細胞内画像処理，文脈情報，輝点検出，ロバスト統計　　Intracellular image processing，contextual information，Light spot detection，Robust statistics

要約(英語): We propose an automatic light spot detection method in intracellular images using contextual information. Light spot detection in intracellular images is important for classification of patients condition. However, light spots are detected manually. Thus, we propose a light spot detection method in intracellular images by computer. In general, supervised learning is used to develop a light spot detector with high accuracy. However, there are the cases in which large number of supervised data are not obtained. In fact, in our research, we have only 4 images with supervised signals. Therefore, we use background subtraction and robust statistics to detect light spots because they do not require supervised signals. However, only unsupervised learning does not give high accuracy. In particular, we can not discriminate light spot and noise well. Therefore, we use contextual information which is obtained from neighboring region of a light spot to reduce noise. In experiments, our method is applied to Wnt-3a images and achieved 80.71% which is higher accuracy than a supervised detector with small number of training images.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.134 No.11 （2014） 特集Ⅰ：電気関係学会関西連合大会　特集Ⅱ：国際会議ヒューマナイズド　システム2013

本誌掲載ページ: 1731-1737 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/134/11/134_1731/_article/-char/ja/