Medical Ultrasound Image Deconvolution

Abstract

In medical pulse-echo ultrasound imaging, a constant sound speed of 1,540 m/s in soft tissues is assumed. When the actual speed is different the mismatch can lead to image distortions. Even if the assumed speed is correct, ultrasound images can be difficult to interpret due to image blurring and the presence of speckle. However, this can be improved by non-blind deconvolution if the point-spread function (PSF) is known. In clinical applications a sufficiently accurate estimate of the PSF is difficult to obtain because of the unknown properties (including speed of sound) of soft tissues. In this paper, we address two topics: first, we explore the sensitivity of our deconvolution algorithm to variations in the speed of sound in the tissue; second, we extend our deconvolution algorithm to enable it to adapt to (and estimate) an unknown sound speed. In the first topic, the results reveal that the deconvolution output is sufficiently sensitive to the accuracy of the sound speed that the speed itself can be estimated using deconvolution. However, qualitative assessment suggests that we may not need the exact speed of sound for successful deconvolution so long as the assumed speed does not deviate significantly from the true value. In the second topic, the goal is gradually to adapt the assumed sound speed to improve the deconvolution and eventually estimate the true sound speed. We tested our algorithm with in vitro phantoms where the estimation error was found to be +0.01 ± 0.60% (mean ± standard deviation). In addition to the speed estimation itself, our method has also proved capable of producing better restoration of the ultrasound images than deconvolution by an assumed speed of 1,540 m/s when this assumption is significantly in error.