19 March 2014 Pre-computed backprojection based penalized-likelihood (PPL) reconstruction with an edge-preserved regularizer for stationary Digital Breast Tomosynthesis
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Abstract
Stationary Digital Breast Tomosynthesis (sDBT) is a carbon nanotube based breast imaging device with fast data acquisition and decent projection resolution to provide three dimensional (3-D) volume information. To- mosynthesis 3-D image reconstruction is faced with the challenges of the cone beam geometry and the incomplete and nonsymmetric sampling due to the sparse views and limited view angle. Among all available reconstruction methods, statistical iterative method exhibits particular promising since it relies on an accurate physical and statistical model with prior knowledge. In this paper, we present the application of an edge-preserved regularizer to our previously proposed precomputed backprojection based penalized-likelihood (PPL) reconstruction. By using the edge-preserved regularizer, our experiments show that through tuning several parameters, resolution can be retained while noise is reduced significantly. Compared to other conventional noise reduction techniques in image reconstruction, less resolution is lost in order to gain certain noise reduction, which may benefit the research of low dose tomosynthesis.
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Shiyu Xu, Shiyu Xu, Christy Redmon Inscoe, Christy Redmon Inscoe, Jianping Lu, Jianping Lu, Otto Zhou, Otto Zhou, Ying Chen, Ying Chen, } "Pre-computed backprojection based penalized-likelihood (PPL) reconstruction with an edge-preserved regularizer for stationary Digital Breast Tomosynthesis ", Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 903359 (19 March 2014); doi: 10.1117/12.2043772; https://doi.org/10.1117/12.2043772
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