SEGMENTED ARRAY RECONSTRUCTIONS FOR TOMOGRAPHIC IMAGING OF LARGE OBJECTS - THEORY AND AN APPLICATION TO NEUTRON COMPUTED-TOMOGRAPHY

In many nondestructive testing applications, high resolution images are desired of large engineering superstructures, such as aircraft. Traditionally, this is done by sequentially imaging small segments of the objects using small area detectors. Recently, we have developed a position sensitive neutron detector system using a LiF-ZnS scintillator screen and a cooled charge coupled device (CCD) camera. Large arrays of these individual detectors can be assembled to image large areas simultaneously at high resolution. For tomography, radiographs are obtained from multiple viewing angles with the large area detector. Tomographic reconstruction of large arrays is prohibitively time consuming and has several associated practical problems. By using the inherent segmentation of the detector, the reconstruction problem can be reduced to one of several small area reconstructions performed in parallel. A parallel tomographic reconstruction scheme based on segmented arrays is presented. It is shown that the parallel algorithm produces images that are identical to images produced without segmentation, however, using smaller individual arrays. The intrinsically parallel segmented array reconstruction provides a means of rapidly reconstructing images of any dimension using small, tractable arrays. An N X N two-dimensional tomographic reconstruction can be performed with m individual detector segments and m2 processors each reconstructing square-root 2 N / m X square-root 2 X N/m image segments. This approach is demonstrated for neutron tomography; however, it is applicable to any tomographic imaging problem.