関連する実験動画

Updated: Sep 9, 2025

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

676

胸部X線画像における肺炎の確固たる検出のための多機能融合を備えた強化されたResNet-50

Neenu Sebastian1, B Ankayarkanni1

  • 1Department of Computer Science and Engineering, School of Computing, Sathyabama Institute of Science and Technology (Deemed to be University), Chennai 600119, India.

Diagnostics (Basel, Switzerland)
|August 28, 2025
PubMed
まとめ

この研究は,胸部X線で肺炎を正確に検出するための最適化されたResNet-50フレームワークを導入します. このモデルは,高度なノイズ削減,マルチ機能の融合,および改善された解釈のための注意力メカニズムを統合することにより,診断の信頼性を高めます.

キーワード:
ResNet-50 について注意力メカニズム胸のX線写真ディープラーニング特徴の融合肺炎の検出質感の特徴

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Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia08:05

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