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19 March 2014Cramér-Rao lower bound in differential phase contrast imaging and its application in the optimization of data acquisition systems
Unlike conventional x-ray absorption imaging, x-ray differential phase contrast imaging (DPCI) uses a phase
retrieval algorithm to obtain x-ray phase information from a group of x-ray intensity measurements. As a result,
the noise performance of DPCI is expected to differ from that of x-ray absorption imaging. Given the total
number of x-ray photons used in imaging, lower noise variance in estimated phase contrast images suggests
superior dose efficiency, which is one of the most desirable feature in x-ray imaging. When an algorithm is used
to retrieve the phase information, it is important to understand what the lowest possible noise variance would
be and whether the algorithm used to retrieve the phase information yields the lowest possible noise variance.
To address these questions for differential phase contrast imaging, we studied the noise performance of DPC
imaging using the powerful Cramér-Rao lower bound (CRLB) in statistical signal estimation method. Results
demonstrated that the noise variances in DPCI images obtained by the algorithmic phase retrieval are always
higher than the CRLB, which implies a possible sub-optimality of current phase estimation method. The results
also call for the need to apply statistical signal estimation theory to DPCI in order to further improve its noise
performance and dose efficiency.
Yongshuai Ge,Ke Li, andGuang-Hong Chen
"Cramér-Rao lower bound in differential phase contrast imaging and its application in the optimization of data acquisition systems", Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90330F (19 March 2014); https://doi.org/10.1117/12.2043930
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Yongshuai Ge, Ke Li, Guang-Hong Chen, "Cramér-Rao lower bound in differential phase contrast imaging and its application in the optimization of data acquisition systems," Proc. SPIE 9033, Medical Imaging 2014: Physics of Medical Imaging, 90330F (19 March 2014); https://doi.org/10.1117/12.2043930