平板探测器
光传递函数
图像分辨率
图像质量
光学
扫描仪
探测器
锥束ct
探测量子效率
迭代重建
帧速率
高动态范围
失真(音乐)
动态范围
材料科学
计算机科学
计算机视觉
物理
医学
放射科
计算机断层摄影术
图像(数学)
放大器
光电子学
CMOS芯片
作者
Yi Ning,Xiangyang Tang,David L. Conover,Rongfeng Yu,Biao Chen,Ruola Ning
出处
期刊:IEEE Transactions on Medical Imaging
[Institute of Electrical and Electronics Engineers]
日期:2000-01-01
卷期号:19 (9): 949-963
被引量:140
摘要
Preliminary evaluation of recently developed large-area flat panel detectors (FPDs) indicates that FPDs have some potential advantages: compactness, absence of geometric distortion and veiling glare with the benefits of high resolution, high detective quantum efficiency (DQE), high frame rate and high dynamic range, small image lag (<1%), and excellent linearity (/spl sim/1%). The advantages of the new FPD make it a promising candidate for cone-beam volume computed tomography (CT) angiography (CBVCTA) imaging. The purpose of this study is to characterize a prototype FPD-based imaging system for CBVCTA applications. A prototype FPD-based CBVCTA imaging system has been designed and constructed around a modified GE 8800 CT scanner. This system is evaluated for a CBVCTA imaging task in the head and neck using four phantoms and a frozen rat. The system is first characterized in terms of linearity and dynamic range of the detector. Then, the optimal selection of kVps for CBVCTA is determined and the effect of image lag and scatter on the image quality of the CBVCTA system is evaluated. Next, low-contrast resolution and high-contrast spatial resolution are measured. Finally, the example reconstruction images of a frozen rat are presented. The results indicate that the FPD-based CBVCT can achieve 2.75-1p/mm spatial resolution at 0% modulation transfer function (MTF) and provide more than enough low-contrast resolution for intravenous CBVCTA imaging in the head and neck with clinically acceptable entrance exposure level. The results also suggest that to use an FPD for large cone-angle applications, such as body angiography, further investigations are required.
科研通智能强力驱动
Strongly Powered by AbleSci AI