基于计算机断层扫描图像分析的COVID-19肺部损伤估计
Martin Schätz1, Olga Rubešová1, Jan Mareš1
1Department of Mathematics, Informatics and Cybernetics, University of Chemistry and Technology, Prague, 166 28, Czech Republic.
F1000Research
|August 22, 2025
概括
这项研究介绍了一种ImageJ工具,用于使用CT扫描量化COVID-19患者的肺部参与. 该软件有助于可重复的患者数据评估和治疗分层.
科学领域:
- 医学成像
- 计算生物学
- 传染病研究
背景情况:
- 现代医疗依赖于可重复的定量数据分析.
- 随着COVID-19大流行,多学科研究的进步,包括患者数据评估的软件.
- 对COVID-19肺部感染的3DCT扫描数据的分析在可视化整体影响和一致性方面存在挑战.
研究的目的:
- 开发并介绍ImageJ软件工具,用于评估COVID-19患者的CT扫描.
- 帮助估计感染的肺组织的百分比.
- 促进客观的患者分层,以便选择合适的治疗方法.
主要方法:
- 在Kralovské Vinohrady医院的放射学中心合作开发了一种专门的ImageJ工具.
- 使用计算机断层扫描 (CT) 进行详细的患者数据评估.
- 实施定量分析以估计肺部感染的百分比.
主要成果:
- 图像J工具使COVID-19患者的CT扫描能够更快,更可复制地进行评估.
- 该软件有助于估计肺部参与的百分比,解决观察者之间的和观察者内部的变异性.
- 患者可以根据量化肺部损伤分为五组.
结论:
- 开发的ImageJ工具为放射科医生和临床医生评估COVID-19肺部影响提供了宝贵的帮助.
- 使用此工具进行定量CT评估支持基于证据的治疗决策.
- 该软件有助于在COVID-19的背景下进行标准化和可重复的患者管理.
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