This paper proposes a comparison between an established (used in magnetic resonance imaging) and a innovative compressed sensing (CS) approach, both adapted to ultrasound (US) imaging. Two undersampling patterns suited to US imaging were investigated in each approach on simulated and in vivo radio-frequency US images. Reconstructions of simulated and in vivo US images using CS show minimal information loss. The best strategy (minimising the errors of reconstruction) was a uniform random sampling in the two directions of the spatial RF US image associated with the reconstruction of its k-space.