Micro-CT imaging of super-resolution MBIR algorithm based on sub-pixel displacement

Abstract

Lens-coupled micro-CT is a common type of high-resolution micro-CT with spatial resolution up to sub-micron. Due to diffraction limit of optical system, mechanical inaccuracy and noise effects in lens-coupled micro-CT, its spatial resolution is difficult to further improve, and its scope of application is also greatly restricted. In this paper, we propose a super-resolution model-based iterative reconstruction (SR-MBIR) algorithm to improve the spatial resolution of micro- CT. The algorithm firstly designs a scanning scheme, in which the scanned object is placed on a high-precision nano stage mounted on the rotation stage, and when the sample is moved in a fixed trajectory, a plurality of projection images with sub-pixel displacement information are obtained. Then based on the MAP reconstruction framework, a sub-pixel displacement model, a blur model and a noise statistical model are incorporated in the forward projection process in reconstruction procedures. By upsampling the data grid and using the sub-pixel displacement information of the projection images in the back projection process, the system resolution can be improved. In the experiment, a bamboo fiber is scanned and reconstructed by the proposed method. Compared with other reconstruction approaches, the result demonstrates that the reconstructed images by the proposed method have sharper boundaries and more details.