Automated quantification of lung pathology on micro-CT in diverse disease models using deep learningResearch in context

Summary: Background: Micro-CT significantly enhances the efficiency, predictive power and translatability of animal studies to human clinical trials for respiratory diseases. However, the analysis of large micro-CT datasets remains a bottleneck. Methods: We developed a generic deep learning (DL)-ba...

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主要な著者:	Flore Belmans, Laura Seldeslachts, Eliane Vanhoffelen, Birger Tielemans, Wim Vos, Frederik Maes, Greetje Vande Velde
フォーマット:	Artigo
言語:	Inglês
出版事項:	Elsevier 2025-09-01
シリーズ:	EBioMedicine
主題:	Lung disease Small animal models Micro-computed tomography Imaging biomarkers Segmentation Deep learning
オンライン･アクセス:	http://www.sciencedirect.com/science/article/pii/S2352396425003482
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