学習による細胞内粒状物質の検出

青木 健太, ヤオカイ フォン, 内田 誠一, 荒関 雅彦, 齋藤 有紀, 鈴木 利治

研究成果: Contribution to journalArticle

抄録

By the development of the microscope, it is now possible to observe the moving APP-GFPs in cells. By observing their movement, the elucidation of causes of diseases, such as Alzheimer, is expected. Presently, quantitative analysis is performed manually with the microscopes and eyes, consuming much effort of researchers. Therefore, in this report, we attempt the detection of APP-GFPs in cells as the first step of the movement analysis of APP-GFPs. Specifically, we perform preprocessing to the cell image for background noise removal, and try the 2-class classification between background and APP-GPP in each pixel. For the classification, we use 1-class support vector machine (OCSVM), which has been often used for pattern detection problems. Through several experimental results, we will observe the difficulties of the detection problem and consider possible remedies for future research.
寄稿の翻訳タイトルDetection of Granular Objects in Cell by Learning
本文言語日本語
ページ(範囲)7-12
ページ数6
ジャーナルIEICE technical report
110
330
出版ステータス出版済み - 12 2 2010

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