Samei Ehsan, Dobbins James T, Lo Joseph Y, Tornai Martin P
Duke Advanced Imaging Laboratories, Duke University Medical Center, Duke University, Durham, NC 27710, USA.
Radiat Prot Dosimetry. 2005;114(1-3):220-9. doi: 10.1093/rpd/nch562.
The transition to digital radiology has provided new opportunities for improved image quality, made possible by the superior detective quantum efficiency and post-processing capabilities of new imaging systems, and advanced imaging applications, made possible by rapid digital image acquisition. However, this transition has taken place largely without optimising the radiographic technique used to acquire the images. This paper proposes a framework for optimising the acquisition of digital X-ray images. The proposed approach is based on the signal and noise characteristics of the digital images and the applied exposure. Signal is defined, based on the clinical task involved in an imaging application, as the difference between the detector signal with and without a target present against a representative background. Noise is determined from the noise properties of uniformly acquired images of the background, taking into consideration the absorption properties of the detector. Incident exposure is estimated or otherwise measured free in air, and converted to dose. The main figure of merit (FOM) for optimisation is defined as the signal-difference-to-noise ratio (SdNR) squared per unit exposure or (more preferably) dose. This paper highlights three specific technique optimisation studies that used this approach to optimise the radiographic technique for digital chest and breast applications. In the first study, which was focused on chest radiography with a CsI flat-panel detector, a range of kV(p) (50-150) and filtration (Z = 13-82) were examined in terms of their associated FOM as well as soft tissue to bone contrast, a factor of importance in digital chest radiography. The results indicated that additive Cu filtration can improve image quality. A second study in digital mammography using a selenium direct flat-panel detector indicated improved SdNR per unit exposure with the use of a tungsten target and a rhodium filter than conventional molybdenum target/molybdenum filter techniques. Finally, a third study focusing on cone-beam computed tomography of the breast using a CsI flat-panel detector indicated that high Z filtration of a tungsten target X-ray beam can notably improve the signal and noise characteristics of the image. The general findings highlight the fact that the techniques that are conventionally assumed to be optimum may need to be revisited for digital radiography.
向数字放射学的转变为提高图像质量带来了新机遇，这得益于新型成像系统卓越的探测量子效率和后处理能力，以及快速数字图像采集所实现的先进成像应用。然而，这种转变在很大程度上并未对用于获取图像的射线照相技术进行优化。本文提出了一个优化数字X射线图像采集的框架。所提出的方法基于数字图像的信号和噪声特性以及所施加的曝光量。根据成像应用中涉及的临床任务，信号被定义为在有代表性背景下有目标和无目标时探测器信号的差值。噪声由均匀采集的背景图像的噪声特性确定，并考虑探测器的吸收特性。入射曝光量在空气中进行估算或以其他方式测量，并转换为剂量。优化的主要品质因数（FOM）定义为每单位曝光量（或更优选地，每单位剂量）的信号差与噪声比（SdNR）的平方。本文重点介绍了三项具体的技术优化研究，这些研究使用该方法对数字胸部和乳腺应用的射线照相技术进行了优化。在第一项研究中，重点是使用碘化铯平板探测器进行胸部X线摄影，研究了一系列千伏峰值（kV(p)）（50 - 150）和滤过（Z = 13 - 82）在其相关品质因数以及软组织与骨骼对比度方面的情况，软组织与骨骼对比度是数字胸部X线摄影中的一个重要因素。结果表明，添加铜滤过可以提高图像质量。第二项关于使用硒直接平板探测器进行数字乳腺摄影的研究表明，与传统的钼靶/钼滤过技术相比，使用钨靶和铑滤过可提高每单位曝光量的SdNR。最后，第三项研究重点是使用碘化铯平板探测器进行乳腺的锥束计算机断层扫描，结果表明钨靶X射线束的高Z滤过可以显著改善图像的信号和噪声特性。总体研究结果凸显了一个事实，即传统上被认为是最佳的技术可能需要重新审视以用于数字放射学。
