人工智能在计算机断层扫描中减少辐射剂量的潜力 - 一个范围审查
M Bani-Ahmad1, A England2, L McLaughlin2
1The Discipline of Medical Imaging and Radiation Therapy, University College Cork, College Road, T12 K8AF Cork, Ireland; Faculty of Applied Medical Sciences, Department of Medical Imaging, The Hashemite University, Zarqa, Jordan.
Radiography (London, England : 1995)
|May 8, 2025
概括
人工智能 (AI) 通过改善患者定位,扫描范围和图像重建来优化计算机断层扫描 (CT) 中的辐射剂量. 这提高了诊断成像的安全性和效率.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 放射学 放射学是一门学科.
背景情况:
- 人工智能 (AI) 正在彻底改变医学成像,特别是计算机断层扫描 (CT).
- 人工智能的影响跨越了诊断成像,为优化提供了新的可能性.
- 本综述侧重于人工智能在CT中减少辐射剂量的作用.
研究的目的:
- 审查和评估人工智能的应用,以优化CT中的辐射剂量.
- 要总结AI在三个关键CT领域的作用:患者定位,扫描范围的确定和图像重建.
主要方法:
- 2018年1月至2024年12月期间发表的文献综合范围审查.
- 在主要的电子数据库 (Scopus,Ovid,EBSCOhost,PubMed) 进行了搜索.
- 数据提取侧重于人工智能应用,辐射剂量指标,解剖区域和评估指标.
主要成果:
- 九十篇文章符合审查的纳入标准.
- 人工智能在优化患者定位和扫描范围方面表现出有效性,减少了手动错误.
- 基于AI的深度学习图像重建改善了低剂量CT图像质量.
结论:
- 人工智能在CT成像中对辐射剂量优化做出了重大贡献.
- 人工智能尽量减少患者定位和过度扫描中的错误.
- 人工智能的临床整合有望在CT协议和剂量降低方面取得进一步的进展.
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