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18 March 2015 Robust iterative image reconstruction for breast CT by use of projection differentiation
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Image reconstruction algorithms for breast CT must deal with truncated projections and high noise levels. Recently, we have been investigating a design of iterative image reconstruction algorithms that employ a differentiation filter on the projection data and estimated projections. The extra processing step can potentially reduce the impact of artifacts due to projection truncation in addition to enhancing edges in the reconstructed volumes. The edge enhancement can improve visibility of various tissue structures. Previously, this idea has been incorporated in an approximate solver of the associated optimization problem. In the present work, we present reconstructed volumes with clinical breast CT data, which result from accurate solution of this optmization problem. Furthermore, we employ singular value decomposition (SVD) to help determine filter parameters and to interpret the properties of the reconstructed volumes.
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David N. Kraemer, Erin G. Roth, Emil Y. Sidky, Ingrid S. Reiser, and Xiaochuan Pan "Robust iterative image reconstruction for breast CT by use of projection differentiation", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94123I (18 March 2015);

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