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- W2037651158 abstract "Diverse physical measurements can be modeled by X-ray transforms. While X-ray tomography is the canonicalexample, reference structure tomography (RST) and coded aperture snapshot spectral imaging (CASSI)are examples of physically unrelated but mathematically equivalent sensor systems. Historically, most x-raytransform based systems sample continuous distributions and apply analytical inversion processes. On the otherhand, RST and CASSI generate discrete multiplexed measurements implemented with coded apertures. Thismultiplexing of coded measurements allows for compression of measurements from a compressed sensing perspective.Compressed sensing (CS) is a revelation that if the object has a sparse representation in some basis,then a certain number, but typically much less than what is prescribed by Shannon's sampling rate, of randomprojections captures enough information for a highly accurate reconstruction of the object. This paper investigatesthe role of coded apertures in x-ray transform measurement systems (XTMs) in terms of data efficiencyand reconstruction fidelity from a CS perspective. To conduct this, we construct a unified analysis using RSTand CASSI measurement models. Also, we propose a novel compressive x-ray tomography measurement schemewhich also exploits coding and multiplexing, and hence shares the analysis of the other two XTMs. Using thisanalysis, we perform a qualitative study on how coded apertures can be exploited to implement physical randomprojections by regularizing the measurement systems. Numerical studies and simulation results demonstrateseveral examples of the impact of coding." @default.
- W2037651158 created "2016-06-24" @default.
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- W2037651158 date "2009-08-20" @default.
- W2037651158 modified "2023-09-23" @default.
- W2037651158 title "Coded aperture computed tomography" @default.
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- W2037651158 doi "https://doi.org/10.1117/12.825277" @default.
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