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M-Count：機械学習の物体検出とカラー閾値処理を利用してムラサキイガイ幼生の計数を行うアプリケーション
Lance W Miller1, Navaj Nune1, Thomas B LeFevre1
1Pacific Northwest National Laboratory, 902 Battelle Blvd, Richland, WA, USA. curtis.larimer@pnnl.gov.
Analytical methods : advancing methods and applications
|January 22, 2026
まとめ
M-Countにより、ムラサキイガイ幼生のようなバイオファウリング生物の定量が、ユーザーフレンドリーなアプリケーションで、より迅速かつ正確になりました。このツールは、個々の生物と集団の両方を効果的に計数し、防汚性能評価を向上させます。
科学分野:
- 海洋生物学
- 材料科学
- 計算生物学
背景:
- バイオファウリングの定量は困難であり、特に個体と塊の両方を形成するムラサキイガイ幼生のような生物にとっては困難です。
- 手動カウントは時間がかかり、既存の自動化された方法は、孤立した生物と集団の両方の生物を検出できないか、非専門家にとってユーザーフレンドリーではありません。
- ムラサキイガイ幼生の定着は、防汚表面性能の重要な指標です。
研究 の 目的:
- ユーザーフレンドリーで、正確なバイオファウリング定量のための機械学習ベースのアプリケーションを開発すること。
- 単一のワークフローで、個々のおよび集団の両方のファウリング生物を検出し定量できるツールを作成すること。
主な方法:
- 個々の生物検出のためのニューラルネットワークと、集団生物検出のためのカラー閾値処理アルゴリズムを統合したアプリケーション、M-Countを開発しました。
- M-Countを、バイオファウリングアッセイからのサンプル表面画像におけるムラサキイガイ幼生の定着を定量化するために適用しました。
- M-Countのパフォーマンスを、手動定量化方法と比較しました。
主要な成果:
- M-Countは、手動カウントと比較して60倍高速であり、大幅な速度向上が実証されました。
- アプリケーションは高い一貫性を示し、バイアスなく繰り返しタスクを実行しました。
- M-Countは良好な精度を維持し、手動カウントの0.209と比較して、正規化平均最大残差は0.220でした。
結論:
- M-Countは、特にムラサキイガイ幼生の場合、バイオファウリング定量のための高速、一貫性があり、正確なソリューションを提供します。
- このアプリケーションのユーザーフレンドリーさと二重検出機能により、防汚表面を評価する非専門家ユーザーに適しています。
- このツールは、生物定着に関する信頼性の高い効率的なデータを提供することにより、防汚戦略の評価を強化します。
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