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An efficient method for accurately calculating the center-of-rotation, or projection center, for parallel computed tomography projection data, or sinograms, is described. This method uses all the data in the sinogram to estimate the center by a least-squares technique and requires no previous calibration scan. The method also finds the object's center-of-mass without reconstructing its image. Since the method uses the measured data, it is sensitive to noise in the measurements, but that sensitivity is relatively small compared to other techniques. Examples of its use on simulated and actual data are included. For fan-beam data over 360 degrees , two related methods are described to find the center in the presence or absence of a midline offset. >

A class of hybrid domain-iterative algorithms for 2-D image reconstruction is described. The consistent iterative reconstruction-reprojection (CIRR) algorithm was designed and implemented along with other classical domain-iterative methods. The algorithms are tested on the hollow projections problem, where simple object models are assumed known. Results show that the CIRR algorithm is robust and accurate, and converges quickly. >

As a result of an arms reduction treaty between the United States and the Russian Federation, both countries will each be storing over 40,000 containers of plutonium. To help detect any deterioration of the containers and prevent leakage, we are designing a digital radiography and computed tomography system capable of handling this volume reliably, efficiently, and at a lower cost.

Members of the Nondestructive Evaluation Section at the Lawrence Livermore National Laboratory (LLNL) are implementing the advanced three-dimensional imaging technique of x- and gamma-ray computed tomography (CAT or CT) for industrial and scientific obscured object evaluation. This technique provides internal and external views of materials, components, and assemblies nonintrusively. Our work includes building of CT scanners as well as data preprocessing, image reconstruction, display and analysis algorithms. These capabilities have been applied to a variety of industrial and scientific NDE applications. We have used CT to study various objects with obscured features at our laboratory ranging in size from 1 mm3 to 1 m3. In these studies, CT has revealed flaws (e.g. cracks, voids, and inclusions), internal and external dimensional information, differences in elemental composition or material density, and other important material characteristics. CT has also been used to localize, identify, and quantify radioisotopes within canisters. As illustrative examples, we describe how CT was instrumental in the analysis of concrete specimens, diesel engine thermocouple plugs, jet engine turbine blades, ballistic target materials, and radioactive waste canisters.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The Systolic Processor with a Reconfigurable Interconnection Network of Transputers (SPRINT) [1] is a sixty-four-element multiprocessor developed at Lawrence Livermore National Laboratory to evaluate systolic algorithms and architectures experimentally. The processors are interconnected in a reconfigurable network which can emulate networks such as the two-dimensional mesh, the triangular mesh, the tree, and the shuffle-exchange network. New systolic algorithms and architectures are described which perform the Radon transform [8] and inverse Radon transform with efficiency arbitrarily close to 100%. High efficiency is possible with any connected network topology, even with low communication bandwidth. The results of the algorithms executed on the SPRINT compare closely with theory.