Stationary head CT with linear CNT x-ray source arrays: image quality assessment through simulation

Abstract

Purpose: Carbon nanotube (CNT) based field-emission x-ray source arrays allow the development of robust stationary computed tomography (CT) imaging systems with no gantry movement. There are many technical considerations that constrain the optimal system design. The aim of this work is to assess the image quality of a proposed Stationary Head CT (sHCT) system through simulation. Methods: In our previous work, we defined a system design consisting of three parallel imaging planes. Each plane consists of a CNT x-ray source array with a large number of linearly distributed focal spots and three strip detector modules. Each imaging plane is rotated 120° with respect to the adjacent plane to provide maximum projection view coverage of the region of interest (ROI). An iterative reconstruction algorithm based on the ASTRA toolbox was developed for the specific sHCT system. The ACR 464 phantom and a set of clinical head CT data were used to assess the system design and image quality. Imaging performance was evaluated both quantitatively and qualitatively. Results: The simulation results suggest that the proposed sHCT design is feasible and high-fidelity CT images can be obtained. The reconstructed image of the ACR 464 phantom reproduces accurate CT numbers. The reconstructed CT images for the human head confirm the capability of this prototype for identifying low contrast pathologies. Conclusion: A three-plane sHCT system is evaluated in this work. The iterative reconstruction algorithm produces high image quality in terms of uniformity, signal-to-noise ratio, signal-to-contrast ratio and structural information. Further work on the optimization of the current sHCT system will focus on speed up of volumetric image data collection in system hardware and further improvement of the reconstruction image quality through regularization and incorporating of machine leaning techniques.