Sequentially optimized projections in x-ray imaging *

نویسندگان

چکیده

This work applies Bayesian experimental design to selecting optimal projection geometries in (discretized) parallel beam X-ray tomography assuming the prior and additive noise are Gaussian. The introduced greedy exhaustive optimization algorithm proceeds sequentially, with posterior distribution corresponding previous projections serving as for determining parameters, i.e. imaging angle lateral position of source-receiver pair, next one. allows redefining region interest after each well adapting parameters (original) measured data. Both A D-optimality considered, emphasis on efficient evaluation objective functions. Two-dimensional numerical experiments demonstrate functionality approach.

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ژورنال

عنوان ژورنال: Inverse Problems

سال: 2021

ISSN: ['0266-5611', '1361-6420']

DOI: https://doi.org/10.1088/1361-6420/ac01a4