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Signal-to-noise and spatial resolution in in-line imaging. 1. Basic theory, numerical simulations and planar experimental images

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arxiv 2312.11506 v1 pith:ZNCLSQ2W submitted 2023-12-11 physics.med-ph physics.optics

classification physics.med-phphysics.optics
keywords propagationexperimentalfree-spaceimagesintensitymethodobjectplane
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Signal-to-noise ratio and spatial resolution are quantitatively analysed in the context of in-line (propagation based) X-ray phase-contrast imaging. It is known that free-space propagation of a coherent X-ray beam from the imaged object to the detector plane, followed by phase retrieval in accordance with Paganin's method, can increase the signal-to-noise in the resultant images without deteriorating the spatial resolution. This results in violation of the noise-resolution uncertainty principle and demonstrates "unreasonable" effectiveness of the method. On the other hand, when the process of free-space propagation is performed in software, using the detected intensity distribution in the object plane, it cannot reproduce the same effectiveness, due to the amplification, during free-space propagation, of photon shot noise in the object-plane intensity. We show that the performance of Paganin's method is determined by just two dimensionless parameters: the Fresnel number and the ratio of the phase shift to the logarithm of intensity in the object plane. The relevant theoretical analysis is performed first, followed by computer simulations and then by a brief test using experimental images collected at a synchrotron beamline. More extensive experimental tests will be presented in the second part of this paper.

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  1. Comparison of three reconstruction algorithms for low-dose phase-contrast computed tomography of the breast with synchrotron radiation

    physics.med-ph 2024-12 conditional novelty 5.0 of 10

    cSART outperforms FBP and UTR on objective image quality metrics in low-dose phase-contrast breast CT, but radiologists prefer FBP images, likely because they weight contrast more heavily than noise.

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