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Application of artificial intelligence to metaphase finder

https://repo.qst.go.jp/records/76768
https://repo.qst.go.jp/records/76768
5fd62881-2a4c-4888-a3c7-916691b1300e
Item type 会議発表用資料 / Presentation(1)
公開日 2019-09-12
タイトル
タイトル Application of artificial intelligence to metaphase finder
言語
言語 eng
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_c94f
資源タイプ conference object
アクセス権
アクセス権 metadata only access
アクセス権URI http://purl.org/coar/access_right/c_14cb
著者 Furukawa, Akira

× Furukawa, Akira

WEKO 783227

Furukawa, Akira

Search repository
Furukawa, Akira

× Furukawa, Akira

WEKO 783228

en Furukawa, Akira

Search repository
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内容記述タイプ Abstract
内容記述 Biological dosimetry is used to estimate individual absorbed radiation dose by quantifying an appropriate biological marker. The most popular gold-standard marker is the appearance of dicentric chromosomes in metaphase. The metaphase finder is a tool for automation of biological dosimetry that finds metaphase cells on glass slides. The author and a software company have designed a new system and are now preparing to produce the system commercially. This system was capable of identifying not only normal chromosomes but also PCC cells. The metaphase finder consists of an automated microscope, an auto-focus system, an X–Y stage, a camera, and a computer.
To enhance the accuracy of the system, an artificial intelligence (AI) with deep learning was tested. The pre-selection of metaphases using mathematical morphology before the AI process was enabled the AI classification of true metaphases or not. A total of 1709 images of the metaphase finder detected as ‘metaphases’ were read into a nine-layer artificial neural network to detect true metaphases. A total of 456 images were used for training, and the rest of the images were used for validation. The accuracy of AI was 0.89 for metaphases and 0.90 for non-metaphases.
Now, implementation of the AI to the metaphase finder is progressing.
会議概要(会議名, 開催地, 会期, 主催者等)
内容記述タイプ Other
内容記述 16th International Congress of Radiation Research
発表年月日
日付 2019-08-27
日付タイプ Issued
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