書誌事項
- タイトル別名
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- Detection of Organs and Identification of Missing Diagnostic Images Using Deep Learning for Assessment of Diagnostic Image Adequacy
説明
<p>The purpose of this study was to evaluate the appropriateness of diagnostic images for automated ultrasound operations. Therefore, two experiments were conducted. The first is to detect the target organ using deep learning. The second is to identify missing parts in the diagnostic images. In the first experiment of organ detection, the IoU and Dice coefficient were 0.947 and 0.972, respectively, indicating high accuracy.In the second experiment to identify the missing parts of the image, the percentage of correct answers for the missing parts on the right side of m was 75.3%, while the percentage of correct answers for the missing parts on the left side was 99.1%.</p>
収録刊行物
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- ロボティクス・メカトロニクス講演会講演概要集
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ロボティクス・メカトロニクス講演会講演概要集 2022 (0), 1P1-M12-, 2022
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390013087507638400
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- ISSN
- 24243124
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可