Performance Optimization of Compressed Sensing Based Synthetic Transmit Aperture Using Hadamard Matrix Encoding

We previously proposed compressed sensing (CS) based synthetic transmit aperture (CS-STA) to reconstruct the synthetic transmit aperture (STA) dataset from a smaller number of randomly apodized plane wave (PW) firings with CS algorithm. However, when uniform random apodization (i.e., measurement matrix) is used, the reconstruction is time-consuming, and the frame rate and image quality improvements are limited. To solve these issues, we propose to use the partial Hadamard matrix as the apodization (i.e., measurement matrix) in this study. Phantom experiments were conducted and the results demonstrated that the partial Hadamard matrix can optimize the performance of CS-STA and further increase the frame rate and image quality of STA.