Li Zhoubo, Leng Shuai, Yu Zhicong, Kappler Steffen, McCollough Cynthia H
Mayo Clinic, Department of Radiology, Rochester, Minnesota, United States.
Mayo Graduate School, Biomedical Engineering and Physiology Graduate Program, Rochester, Minnesota, United States.
J Med Imaging (Bellingham). 2017 Apr;4(2):023505. doi: 10.1117/1.JMI.4.2.023505. Epub 2017 Jun 22.
Photon-counting detector CT has a large number of acquisition parameters that require optimization, particularly the energy threshold configurations. Fast and accurate estimation of both signal and noise in photon-counting CT (PCCT) images can facilitate such optimization. Using the detector response function of a research PCCT system, we derived mathematical models for both signal and noise estimation, taking into account beam spectrum and filtration, object attenuation, water beam hardening, detector response, radiation dose, energy thresholds, and the propagation of noise. To determine the absolute noise value, a noise lookup table (LUT) for all available energy thresholds was acquired using a number of calibration scans. The noise estimation algorithm then used the noise LUT to estimate noise for scans with a variety of combination of energy thresholds, dose levels, and object attenuations. Validation of the estimation algorithms was performed on a whole-body research PCCT system using semianthropomorphic water phantoms and solutions of calcium and iodine. Clinical feasibility of noise estimation was assessed with scans of a cadaver head and a living swine. The algorithms achieved accurate estimation of both signal and noise for a variety of scanning parameter combinations. Maximum discrepancies were below 15%, while most errors were below 5%.
光子计数探测器CT有大量需要优化的采集参数,尤其是能量阈值配置。快速准确地估计光子计数CT(PCCT)图像中的信号和噪声有助于进行这种优化。利用一台研究型PCCT系统的探测器响应函数,我们推导了信号和噪声估计的数学模型,其中考虑了线束光谱和过滤、物体衰减、水的线束硬化、探测器响应、辐射剂量、能量阈值以及噪声的传播。为了确定绝对噪声值,使用多次校准扫描获取了所有可用能量阈值的噪声查找表(LUT)。然后,噪声估计算法使用噪声LUT来估计具有各种能量阈值、剂量水平和物体衰减组合的扫描的噪声。使用半人体水模以及钙和碘溶液,在一台全身研究型PCCT系统上对估计算法进行了验证。通过对一具尸体头部和一头活猪的扫描评估了噪声估计的临床可行性。对于各种扫描参数组合,这些算法实现了对信号和噪声的准确估计。最大差异低于15%,而大多数误差低于5%。