Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China.
School of Nuclear Science and Technology, University of Chinese Academy of Sciences, Beijing, China.
J Xray Sci Technol. 2023;31(4):811-824. doi: 10.3233/XST-230054.
Photon counting spectral CT is a significant direction in the development of CT technology and material identification is an important application of spectral CT. However, spectrum estimation in photon counting spectral CT is highly complex and may affect quantification accuracy of material identification.
To address the problem of energy spectrum estimation in photon-counting spectral CT, this study investigates empirical material decomposition algorithms to achieve accurate quantitative decomposition of the effective atomic number.
The spectrum is first calibrated using the empirical dual-energy calibration (EDEC) method and the effective atomic number is then quantitatively estimated based on the EDEC method. The accuracy of estimating the effective atomic number of materials under different calibration conditions is investigated by designing different calibration phantoms, and accurate quantitation is achieved using suitable calibration settings. Last, the validity of this method is verified through simulations and experimental studies.
The results demonstrate that the error in estimating the effective atomic number is reduced to within 4% for low and medium Z materials, thereby enabling accurate material identification.
The empirical dual-energy correction method can solve the problem of energy spectrum estimation in photon counting spectral CT. Accurate effective atomic number estimation can be achieved with suitable calibration.
光子计数能谱 CT 是 CT 技术发展的一个重要方向，材料识别是光谱 CT 的一个重要应用。然而，光子计数能谱 CT 中的能谱估计非常复杂，可能会影响材料识别的定量准确性。
针对光子计数能谱 CT 中的能谱估计问题，本研究探讨了经验材料分解算法，以实现有效原子序数的精确定量分解。
首先使用经验双能校准（EDEC）方法对谱进行校准，然后基于 EDEC 方法定量估计有效原子序数。通过设计不同的校准体模，研究了不同校准条件下材料有效原子序数估计的准确性，并采用合适的校准设置实现了精确的定量。最后，通过模拟和实验研究验证了该方法的有效性。
结果表明，对于低 Z 和中 Z 材料，有效原子序数的估计误差降低到 4%以内，从而实现了精确的材料识别。
经验双能校正方法可以解决光子计数能谱 CT 中的能谱估计问题。通过合适的校准，可以实现有效原子序数的精确估计。
