摘要
目的基于ACR体模对MRI系统进行质量控制,设计图像信噪比(Signal to Noise Ratio,SNR)及均匀度自动测量软件,提高质控检测参数测算的效率。方法基于ACR体模质控检测SNR及图像均匀度测算方法,并根据图像特征,在Matlab R2013b平台设计编写图像预处理、特征提取等算法,实现对SNR及图像均匀度自动化处理及分析,并采用Bland-Altman统计学方法评价手工测算与自动测量两种方法的一致性。结果基于Matlab R2013b平台设计编写的自动检测程序实现了对SNR及图像均匀度的自动测量,Bland-Altman图显示,手工测算和自动测算测得的SNR的数据点均位于一致性界限的范围内(-53.1,40.5),图像均匀度的数据点均位于一致性界限的范围内(-4.7%,3.0%),说明两种方法的一致性较好。结论基于Matlab平台的自动化评估算法易于实现,可极大提高质控参数测算效率,有望与手工测量相互替代。
Objective Based on the quality control of magnetic resonance imaging system using ACR volume model,to design the image signal to noise ratio(SNR)and uniformity automatic measurement software to improve the efficiency of measuring quality control parameters.Methods Based on the SNR and uniformity measurement method of ACR body model quality control detection image,and according to image characteristics,image preprocessing and feature extraction algorithms were designed and written on Matlab R2013b platform to realize automatic processing and analysis of SNR and uniformity of image.Bland-altman statistical method was used to evaluate the consistency between manual measurement and automatic measurement.Results The automatic detection program designed and written based on Matlab R2013b platform realized the automatic measurement of SNR and image uniformity.The Bland-Altman diagram showed that the data of the SNR measured by manual measurement and automatic measurement were within the range of the consistency limit(-53.1,40.5),and the data of the image uniformity were within the range of the consistency limit(-4.7%,3.0%),indicating that the consistency of the two methods was good.Conclusion The automatic measurement software based on Matlab platform is easy to implement,can greatly improve the efficiency of quality control parameter measurement,and is expected to replace manual measurement.
作者
陈佳敏
梁永刚
叶培筠
陈楚洁
付丽媛
CHEN Jiamin;LIANG Yonggang;YE Peiyun;CHEN Chujie;FU Liyuan(Department of Radiology,Fuzong teaching hospital,Fujian University of Traditional Chinese Medicine,Fuzhou Fujian 350025,China;Department of Radiology,The 900th Hospital of Joint Logistics Support Force,Fuzhou Fujian 350025,China;General Hospital of Eastern Theater Command,Nanjing Jiangsu 210002,China)
出处
《中国医疗设备》
2022年第8期160-163,172,共5页
China Medical Devices
基金
福建省科技计划项目(2021I0037)
医院科研计划(2019Q02)。