Time domain compressive beamforming: Application to in-vivo echocardiography

In this contribution we refined our previously introduced time domain compressive beamforming algorithm (t-CBF). Our aim was to make t-CBF less greedy in terms of memory usage to be able to adapt it to real life images. Along the way, we also introduced necessary adjustments to further sparsify our images and make the reconstruction more robust in the presence of speckle. The wavelet transform was implemented in t-CBF in different flavors both in terms of wavelet family and decimated/undecimated algorithm. The cardiac dataset used in this contribution corresponds theoretically to a single diverging wave insonification. Compared to the performance of classic DAS in the same setting, t-CBF yielded better contrast, less sidelobes, and cleaner images.