In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent...In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.展开更多
针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,...针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,从而更好地平衡算法的全局搜索能力和局部搜索能力;同时,在算法的位置更新公式中引入S型函数,并利用个体粒子自身的适应度值与群体平均适应度值的比值自适应地调整搜索步长,从而提高算法的搜索效率。在若干经典测试函数上的仿真实验结果表明,与已有的几种改进粒子群算法相比,SAPSO在收敛速度和求解精度方面均有较大优势。展开更多
文摘In a dynamic CT, the acquired projections are corrupted due to strong dynamic nature of the object, for example: lungs, heart etc. In this paper, we present fan-beam reconstruction algorithm without position-dependent backprojection weight which compensates for the time-dependent translational, uniform scaling and rotational deformations occurring in the object of interest during the data acquisition process. We shall also compare the computational cost of the proposed reconstruction algorithm with the existing one which has position-dependent weight. To accomplish the objective listed above, we first formulate admissibility conditions on deformations that is required to exactly reconstruct the object from acquired sequential deformed projections and then derive the reconstruction algorithm to compensate the above listed deformations satisfying the admissibility conditions. For this, 2-D time-dependent deformation model is incorporated in the fan-beam FBP reconstruction algorithm with no backprojection weight, assuming the motion parameters being known. Finally the proposed reconstruction algorithm is evaluated with the motion corrupted projection data simulated on the computer.
文摘针对粒子群算法求解精度低和后期收敛速度慢等问题,提出了一种基于S型函数的自适应粒子群优化算法SAPSO (S-shaped function based Adaptive Particle Swarm Optimization)。该算法利用倒S型函数的特点,实现了对惯性权重的非线性调整,从而更好地平衡算法的全局搜索能力和局部搜索能力;同时,在算法的位置更新公式中引入S型函数,并利用个体粒子自身的适应度值与群体平均适应度值的比值自适应地调整搜索步长,从而提高算法的搜索效率。在若干经典测试函数上的仿真实验结果表明,与已有的几种改进粒子群算法相比,SAPSO在收敛速度和求解精度方面均有较大优势。
