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Updated: Feb 22, 2026

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.6K

ウェブベースのワークフロープラットフォームを使用してCTの腎臓石検出のためのディープラーニングモデルの将来のパイロット評価

Coşku Öksüz1

  • 1Department of Electrical and Electronics Engineering, Faculty of Engineering and Architecture, Izmir Bakırçay University, İzmir, Turkey. cosku.oksuz@bakircay.edu.tr.

International urology and nephrology
|February 21, 2026
PubMed
まとめ

この研究では,人工知能による腎石検出モデルを,シミュレートされた放射線学のワークフローで将来的に評価し,高い精度と信頼性を実証しました. この発見は,診断効率の向上のためにAIを臨床実務に統合することを支持しています.

キーワード:
臨床的意思決定支援についてクリニカルワークフローの統合ディープラーニングとは,ディープラーニングです.腎臓石検知器 腎臓石検知器 腎臓石検知器コントラストのないCTCTです.将来のパイロット研究に関する見通しウロリチアシス (Urolithiasis) とは

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