Sub-Pixel Compounding From Elasticity Imaging Data

摘要

Sub-pixel compounding is a technique that synthesizes the information of an image sequence to form a better-resolved and speckle reduced image. To avoid extra data acquisition time and patient exposure, reuse of the existing data is highly desired. In elasticity imaging, a set of images with slight changes due to deformation is produced, which provides an ideal input for the sub-pixel compounding process. In this paper, a brief review of the resolution enhancement techniques in ultrasound imaging will be provided, and then, a diffusion-regularized, least square approach is presented for sub-pixel compounding image reconstruction. Based on the results, we suggest that (1) B-mode images from elastic imaging are suitable data for sub-pixel compounding and a speckle noise reduced higher-resolution image is a co-product of elasticity imaging; (2) for breast diagnosis, resolution improvement is of strong interest since better depiction of the interior and exterior structures of a tumor provides important detection and diagnostic information; (3) a similar approach could be extended to elasticity imaging with other modalities.