Constrained least squares filtering for ultrasound image deconvolution

This paper uses a new tissue model, which incorporates random fluctuations of the tissue signal within the received ultrasound radio frequency (RF) echo signal, to propose an ultrasound image deconvolution algorithm for improving the quality of ultrasound images. Using this model, we propose a modified version of the classical regularization method which combines optimal Wiener filter and constrained least squares (LS) filtering algorithm for estimation of the tissue signal. The performance of the algorithm is evaluated by simulation. The deconvolved images can show significant improvement in both the speckle reduction and the contrast ratio.