Abstract
In this manuscript, we present experimental results from a nondestructive evaluation (NDE) system that is being used to inspect naval munition components, such as missile rocket motors. The X-ray computed tomography–based NDE (CT-NDE) system was developed by the NDE group at the Indian Head Division, Naval Surface Warfare Center (NSWC) in Indian Head, MD. The maximum likelihood (ML) method has been used successfully to reconstruct transmission images in a medical imaging modality known as positron emission tomography. Motivated by this fact, we use the ML method to reconstruct transmission images for the CT-NDE system at the Indian Head Division, NSWC and investigate its performance using experimental studies. From these studies, we preliminarily conclude that the ML method reconstructs transmission images with good quantitative accuracy and significant detail, even when there is limited angular sampling.
Notes
1We developed an algorithm that converged slower than the proposed one and had a higher cost per iteration using a majorization function based on the following result: