  Synthetic transmit aperture (STA) ultrasound imaging is well known for ideal
focusing in the full field of view. However, it suffers from low
signal-to-noise ratio (SNR) and low frame rate, because each array element must
be activated individually. In our previous study, we encoded all the array
elements with partial Hadamard matrix and reconstructed the complete STA
dataset with compressed sensing (CS) algorithm (CS-STA). As all the elements
are activated in each transmission and the number of transmissions is smaller
than that of STA, this method can achieve higher SNR and higher frame rate. Its
main drawback is the time-consuming CS reconstruction. In this study, we
accelerate the complete STA dataset reconstruction with minimal l2-norm least
square method. Thanks of the orthogonality of partial Hadamard matrix, the
minimal l2-norm least square solution can be easily calculated. The proposed
method is tested with simulation data and experimental phantom and in-vivo
data. The results demonstrate that the proposed method achieves ~5*10^3 times
faster reconstruction speed than CS algorithm. The simulation results
demonstrate that the proposed method is capable of achieving the same accuracy
for STA dataset reconstruction as conventional CS-STA method. The simulations,
phantom and in-vivo experiments show that the proposed method is capable of
improving the generalized contrast-to-noise ratio (gCNR) and SNR with
maintained spatial resolution and fewer transmissions, compared with STA. In
conclusion, the improved image quality and reduced computational time of LS-STA
pave the way for its real-time applications in the clinics.
