计算机层析(CT)扫描过程中,为了加快速度,同时减少X射线对人体的伤害,在有限角度下采样少量的投影数据进行不完全数据重建就显得非常重要。基于总变分最小化的图像迭代重建算法,能够较好地应用于有限角度CT重建,然而,其最小化函数的权值参数必须通过大量的实验观察比较才能被确定。即便这样,得到的参数往往也不是最优的。为此,引入了一种基于乘性正则化的迭代重建算法,将总变分函数作为最小化函数的一个因子,在具有总变分方法优点的同时,能够在迭代过程中自适应地调整正则化参数。仿真实验验证了该算法的有效性。

In the applications of tomographic imaging,insufficient data reconstruction using few projections from limited angle is very important,because it would enable rapid scanning with reduced X-ray doses delivered to patients. The iterative image reconstruction algorithm based on the minimization of the image total variation (TV) works well for limited-angle reconstruction problem. However,the weighting parameter in the cost function can only be determined through considerable experimentation and the parameter attained is not always the optimum. An iterative image reconstruction algorithm based on multiplicative regularization method is introduced. The method obtains the advantages of the TV method by introducing the TV as a multiplicative factor in the cost function,and it can also self-adaptively adjust the regularization parameter during the iterative process. Simulation results show that the proposed algorithm works effectively.