Image Reconstruction for Stationary Head CT with CNT X-ray Source Arrays

The rapid diagnosis of traumatic brain injuries is of paramount importance in resource-poor environments. Current CT systems are highly complex instruments with rapid rotation of the gantry, which limits the acquisition time and introduces motion artifacts. The invention of carbon nanotube x-ray source arrays has enabled the development of novel imaging systems, including stationary tomosynthesis and stationary computed tomography with fast data acquisition, mechanically robust structures, and reduced image blur from source-detector motion. In this work, we explore the feasibility of building a s-HCT system using commercially available CNT linear x-ray sources and build a data processing package for image reconstruction and analysis for the designed system. At the initial stage of developing the system, this work involved both simulation and basic experimentation study. A data processing and image reconstruction package was developed to investigate the optimal system configuration of the s-HCT and the best approach to achieve high-fidelity images. System configurations were assessed qualitatively and quantitatively from both sinogram coverage and reconstructed image quality perspectives. The final implementation of the prototype s-HCT system was evaluated and improved on its performance for head imaging. Our simulation studies suggest that a s-HCT system using three CNT x-ray source arrays could achieve sufficient sinogram coverage to generate reconstructed images with accurate CT numbers and detectability on low-contrast features. Iterative reconstruction algorithms were implemented for reduced-projection reconstruction. Such a system prototype has been implemented in a benchtop setting. 3D volumetric data can be acquired and reconstructed with the proposed data processing package for the s-HCT system. Preliminary evaluations indicated the system could generate images with good uniformity, high spatial resolution, and detectability on high-resolution features. Improvements on system noise were undertaken to achieve better image quality and detection on low-resolution soft tissues in head imaging. This work includes a comprehensive comparison of stationary CT to standard imaging approaches. Geometry configurations for head CT utilizing linear CNT source tubes were first investigated with a specifically developed data processing package. Under the guidance of simulation results, a proof-of-concept system is first developed and characterized. A clinical setup of the system is under construction and has been approved by IRB for clinical trials.Doctor of Philosoph