Desing of a coded aperture base computed tomography architecture with two X-ray rotating sources

Abstract

Computed tomography (CT) is a non-destructive technique that allows estimation and visualization of the internal structure of an object. Traditionally, CT images are captured by a CT scanner. However, different factors reduce the quality of the acquired images. To obtain a high quality CT images is necessary increase the number of sensors or oversample the object. The number of projections needed for sensing a CT scene is determined by the Nyquist limit, however, in some cases the imposed projections number is excessive. Coded aperture are elements that can block or allow the passing of X-rays and is one approach that can overcome these limitations. Compressive sensing (CS) has emerged as a sampling technique requiring fewer projections than those specified by the Nyquist criterion. CS is a theory to acquire and to reconstruct a signal efficiently by the search of a sparse solution to an indeterminate system of linear equations. A strategy to introduce CS theory in a CT configuration is to include elements into the system that allow coding the measurements to get compressed samples. This paper describes a CS system for CT based on coded apertures using two sources and a two-dimensional array that rotate around the object. An optimized value of transmittance and an aperture distribution are selected such that the quality of reconstruction is efficient. In order to compare the performance of the proposed method, two real CT images and two synthetic CT image were used. Simulations indicate that CT architecture provides comparable results to those achieved with traditional CT architectures. The simulation results show that the proposed method allows more diversity coding. This allows up to 2 dB improvement in terms of PSNR than the results obtained using traditional architecture cone beam.