Retrieval of multiple scattering contrast from x-ray analyzer-based imaging

doi:10.1088/1674-1056/abbbed

Abstract We present a moment-based alternative approach to retrieve multiple scattering contrasts from x-ray analyzer-based imaging. By use of the properties of moments of convolutions, the multiple-image radiography approach is theoretically validated. Furthermore, higher order moments of the object scattering distribution, inaccessible in multiple-image radiography, are simultaneously provided by this alternative approach. It is experimentally demonstrated that the skew and kurtosis information related to the distribution of sub-pixel features within the object can be obtained from those complementary contrasts. Finally, the sensitivity of the retrieved multiple scattering contrasts is investigated experimentally. The finding that the sensitivity is inversely proportional to the square root of the detected photon number essentially indicates that the retrieval of moments with an order higher than two can be achieved without increasing exposure time or dose. The presented alternative approach provides an access to the exploitation of multiple scattering contrasts, which is expected to be useful in biomedical research, materials science, security screening, etc.

Keywords: x-ray imaging analyzer-based imaging rocking curve moment analysis

Received: 06 June 2020
Revised: 02 September 2020
Accepted manuscript online: 28 September 2020

PACS:	87.59.-e	(X-ray imaging)
	42.30.Va	(Image forming and processing)
	41.50.+h	(X-ray beams and x-ray optics)
	87.57.N-	(Image analysis)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 11475170, U1532113, and 11905041) and the Fundamental Research Funds for the Central Universities, China (Grant No. PA2020GDKC0024).

Corresponding Authors: ^†Corresponding author. E-mail: dywangzl@hfut.edu.cn

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Heng Chen(陈恒), Bo Liu(刘波), Li-Ming Zhao(赵立明), Kun Ren(任坤), and Zhi-Li Wang(王志立) Retrieval of multiple scattering contrast from x-ray analyzer-based imaging 2021 Chin. Phys. B 30 018701

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