Parametric Phase Information based 2D Cepstrum PSF Estimation Method for Blind De-convolution of Ultrasound Imaging

摘要

In the ultrasound imaging system, blurring which occurs after passing through ultrasound scanner system, represents point spread function (PSF) that describes the response of the ultrasound imaging system to a point source distribution. So, de-blurring can be achieved by de-convolving the ultrasound images with an estimated of corresponding PSF. However, it is hard to attain an accurate estimation of PSF due to the unknown properties of the tissues of the human body through the ultrasound signal propagates. In this paper, we present a new method for PSF estimation in the Fourier domain (FD) based on parametric minimum phase information, and simultaneously, it performs fast 2D de-convolution in the ultrasound imaging system. Although most of complex cepstrum methods, are obtained using complex 2D phase unwrapping in order to estimate the FD-phase information of PSF, our algorithm estimates the 2D PSF using 2D FD-phase information with the parametric weighting factor α and β. They affect the feature of PSF shapes. This makes the computations much simpler and the estimation more accurate. Our algorithm works on the beam-formed uncompressed radio-frequency data, with pre-measured and estimated 2D PSFs database from actual probe used. We have tested our algorithm with vera-sonic system and commercial ultrasound scanner (Philips C4-2), in known speed of sound phantoms and unknown speeds in vivo scans.