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Automated contrast-to-noise ratio analysis in chest CT: validation of an open-source segmentation approach

Abstract Objectives This study aimed to evaluate the feasibility and accuracy of automated contrast-to-noise ratio (CNR) analysis in chest CT using the open-source body and organ analysis (BOA) framework and to validate segmentation modifications for reproducible image-quality assessment. Materials...

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Збережено в:
Автори: Nikolas Beck, Giulia Baldini, Luca Salhöfer, René Hosch, Sebastian Zensen, Marcel Opitz, Denise Bos, Jannis Straus, Michael Forsting, Felix Nensa, Lale Umutlu, Johannes Haubold, Mathias Holtkamp
Формат: Artigo
Мова:Inglês
Опубліковано: SpringerOpen 2026-04-01
Серія:Insights into Imaging
Предмети:
Artificial intelligence
Tomography (X-ray computed)
Image interpretation (computer-assisted)
Quality assurance (health care)
Body and organ analysis
Онлайн доступ:https://doi.org/10.1186/s13244-026-02263-y
Теги: Додати тег
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