Two-dimensional blind iterative deconvolution of medical ultrasound images

The paper presents a new approach to two-dimensional (2D) blind deconvolution of ultrasonic images. Homomorphic deconvolution, so far the most successful method in this field, is based on the assumption that the point spread function (PSF) and the tissue signal lie in different bands of the cepstrum domain, which is not completely true. Furthermore, 2D phase unwrapping is necessary in 2D homomorphic mapping, which is an ill-posed and noise-sensitive problem. Here both limitations are avoided using blind iterative deconvolution namely Van Cittert algorithm with reblurring. Simplified homomorphic deconvolution is used only for initial estimation. The algorithm is applied to the whole radiofrequency image, meaning that only the global spatially invariant component of the PSF is removed. Tests on synthetic and clinical images have shown that the deconvolution gives stable results of clearly higher spatial resolution and better defined tissue structures than in the input images.