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Fast High Resolution Algorithms for Nondestructive Evaluation Computed Tomography

The expectation-maximization (EM) algorithm is an iterative computed tomography (CT) algorithm, introduced in the 1980's for positron emission tomography (PET) [Shepp, 1982]. We developed a variant of this algorithm for nondestructive evaluation x-ray CT [Holmes, 2010, 2011, 2012]. It shows capabilities to improve image fidelity, including resolving power and contrast. A historical challenge has been processing time. We developed improvements so that processing times are approaching those of the filtered backprojection (FBP) algorithm. This is accomplished, in part, by the parallel computation using graphical processing units (GPU's). It is also due to a novel variant of the ordered subsets algorithm extensions [Hudson]. We call this novel variant the fast EM ordered subsets (FEMOS) algorithm. Resolving power is accomplished that shows details not seen by FBP and exceeds the standard pixel resolution.

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