评估定位精度,辐射剂量和图像质量:基于人工智能的自动定位与CT KUB手动定位
Souradip Kundu1, Kaushik Nayak1, Rajagopal Kadavigere2
1Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
F1000Research
|July 4, 2024
概括
人工智能 (AI) 在CT KUB成像中的自动定位可以提高精度和图像质量,同时减少辐射剂量. 这种人工智能方法提高了放射学中的患者护理和诊断效率.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 放射学领域的创新增强了患者服务.
- 人工智能 (AI) 通过减少扫描时间,改善患者定位,降低辐射剂量 (RD) 和提高图像质量 (IQ) 来帮助优化计算机断层扫描 (CT) 成像.
研究的目的:
- 评估和比较基于AI的自动定位 (AP) 和手动定位 (MP) 技术之间的定位精度,辐射剂量 (RD) 和图像质量 (IQ),用于CT脏尿道和膀 (CT KUB) 检查.
主要方法:
- 一项涉及每组143名患者的前性研究:手动定位 (MP) 和基于人工智能的自动定位 (AP) 对CT KUB.
- 两个组都使用了标准化的扫描协议.
- 评估包括离中心距离,RD和定量/定性智商参数.
主要成果:
- 与MP组 (15.12±9.55毫米) 相比,基于AI的AP组显示患者离中心距离 (9.66±6.361毫米) 显著减少.
- 在AP组中观察到RD显著减少.
- 在AP组显示较低的图像噪声 (IN),更高的信号噪声比 (SNR) 和对比噪声比 (CNR) (p<0.05).
- 在AP组中,包括IN,度和整体智商在内的定性智商参数显著更好 (p<0.05).
结论:
- 基于人工智能的自动定位提供了卓越的定位准确性,与手动定位相比,减少了44%的离中心距离.
- 这种人工智能方法使得CT KUB成像的辐射剂量 (RD) 减少12%,图像质量 (IQ) 提高.
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