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基于模型的代重建对胸部计算机断层扫描对COVID-19肺炎的图像质量的影响

Caiyin Liu¹, Junkun Lin¹, Yingjie Chen¹

¹From the Department of Radiology, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China.

Journal of computer assisted tomography

|June 26, 2024

概括

与传统方法相比,FIRST-LUNG-MILD重建算法显著提高了COVID-19肺炎的胸部CT图像质量,提供了更好的肺结构和病变可视化.

科学领域:

放射学放射学是一门学科.
医疗成像医学成像
计算成像技术的成像

背景情况:

在胸部CT成像中,COVID-19肺炎带来了诊断挑战.
像过后投影 (FBP) 和混合代重建 (HIR) 这样的传统重建方法在图像质量方面存在局限性.

研究的目的:

使用FIRST-LUNG (基于前模型的代重建解决方案-LUNG) 对FBP和HIR进行的COVID-19肺炎胸部CT扫描的图像质量进行比较.

主要方法:

从44名COVID-19肺炎患者的CT图像进行了回顾性分析.
使用FBP,HIR和FIRST-LUNG (MILD/STANDARD/STRONG) 的重建.
进行了客观 (CT值,噪声,SNR,CNR,基于任务的传输函数) 和主观的图像质量评估.

主要成果:

第一个肺的重建显示噪声明显低,SNR/CNR高于FBP和HIR (P<0.001).
与FBP和HIR相比,FIRST-LUNG-MILD/STANDARD实现了优越的整体图像质量和更好的肺结构和病变可视化 (P <0.05).
基于任务的转移函数值在FIRST重建中始终较高.

结论:

第一肺中/标准算法提高了COVID-19肺炎患者的胸部CT图像质量.
建议使用FIRST-LUNG-MILD诊断COVID-19肺炎,因为其优越的图像质量和病变细节的保存.

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