Abstract
X-ray computed tomography (CT) plays a crucial role in enhancing national
security. The use of x-ray active interrogation can give insight on the structure of an
object and its material density to provide an effective means of detecting potential
threats in a wide range of objects. A small and lightweight portable CT device that
can address highly sensitive inputs is constructed to perform active interrogation.
Preprocessing analysis is performed to calibrate for irregularities in pixel values,
detector current, tilt corrections, and more. Full image acquisitions are obtained with
different x-ray source energy levels, two separate spot sizes, and different placements
of the imaging object, aiming to assess the optimal parameters for achieving high
image resolution. The Feldkamp-Davis-Kress (FDK), the Regularized Weighted Least
Squares (RWLS), and the Adaptive Steepest Descent Projection onto Convex Sets
(ASD-POCS) were the various reconstruction algorithms examined and compared to
assess which yielded the highest spatial resolution in the resulting outputs. These
algorithms are compared for reconstructions applied between 10 and 600 images
acquired between 0° to 360°. Ideal parameters were identified and applied to enhance
the tomographic reconstruction output, considering these variations in the number of
images per acquisition.
