合成孔径压缩感知超声成像中的高效能稀疏字典设计

针对目前常见的稀疏字典缺乏针对性,在合成孔径医学超声成像中的应用效果不佳,难以在低压缩率下保证重构图像质量的问题,本文设计了一种高效能的稀疏字典。根据超声回波信号是由发射脉冲信号经过不同延时衰减后叠加的特点,利用发射脉冲作为基函数构造稀疏字典,回波信号在该稀疏字典确定的变换域中具备很好的稀疏性,理论上能使其稀疏表示系数的稀疏度等于超声阵元接收到的反射回波数。通过FieldⅡ对简单点目标和复杂目标的仿真结果表明:在相同的重构算法和压缩率下该稀疏字典重构的平均绝对误差明显小于常见的稀疏字典,其值仅为DWT的几分之一,DFT和DCT的几十分之一,能让回波信号以更低的压缩率实现相同的恢复效果。本文最后使用体模的实际采集数据对算法的实际效果进行检测,实验结果也与仿真结果基本一致。基于该稀疏字典的压缩感知算法可以进一步减少合成孔径成像所需存储的数据量、降低系统的复杂度。

The design of a high efficient sparse dictionary in synthetic transmit aperture of ultrasound imaging

Due to conventional sparse representation bases are not targeted, so the application in synthetic transmit aperture medical ultrasound imaging is not efficient, and it's hard to guarantee the reconstruction effect with a low compression ratio, A high efficient sparse dictionary is designed to solve the problem. Based on the properties of ultrasound echo signals, the dictionary uses transmitted pulse as the basis function, sparse representations of echo signals on the proposed sparse dictionary is very sparsity and theoretically the sparsity of sparse coefficients can be equal to the number of reflection signals. Simulations of the simple point targets and the complex targets through the simulation tool Field Ⅱ demonstrate that the mean absolute error using the sparse dictionary is obvious smaller with the same reconstruction algorithm and compression ratio compared to conventional sparse representation, it is a fraction of DWT and it is a few one-tenth and even a few percent of DCT and DFT. The sparse dictionary can reach the same recovery effect by a lower compression ratio. Finally, an experiment is conducted on the basis of the actual data. The experimental result is also in line with the simulation. The compressed sensing method based on the proposed sparse dictionary can furtherly reduce the complexity of system and the amount of acquired echo data needed to reconstruct the ultrasound imaging