基于粒子群算法的CT系统参数标定及优化

Parameter Calibration and Optimization of CT System Based on Particle Swarm Optimization

本文针对CT系统参数标定及成像问题,利用CT系统成像原理,得到CT系统参数与探测器接受信息的关系,建立相关的数学模型。基于螺旋CT原理,利用简单的几何关系,有效地求解出CT系统模板的参数,较好地实现了CT系统参数标定。在此基础上利用经典Radon变换求解出未知介质的几何信息和吸收率信息,解决了未知介质的模型重建的问题。最后特别引入粒子群算法实现五个参数的调节优化,并设计和优化了新的模板,解决了原模板设计可采集的数据较少的问题,精度和稳定性都有明显的改善。

Aiming at the calibration and imaging problems of CT system,the relationship between the parameters of CT system and the information received by the detector is obtained by using the imaging principle of CT system,and the related mathematical models are established.Based on the principle of spiral CT,the parameters of the template of the CT system are effectively solved by using the simple geometric relation,and the parameter calibration of the CT system is realized.On this basis,the classical Radon transform is used to solve the geometric information and absorptivity information of the unknown medium,and the problem of the model reconstruction of the unknown medium is solved.Finally,particle swarm optimization is introduced to optimize and optimize the five parameters.The new template is designed and optimized to solve the problem of less data collected from the original template design,and the accuracy and stability have been improved significantly algorithm.