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Proceedings Paper

Low-dose x-ray tomography using photon-counting detector (Conference Presentation)
Author(s): Zheyuan Zhu; Sean Pang

Paper Abstract

The radiation dosage delivered to the sample is a constant challenge facing X-ray imaging systems. In conventional transmission-based computed tomography (CT), a beam penetrating through thick, high-attenuation region in the sample results in low signal on the detector, and therefore a higher power (e.g., tube current modulation) or longer integration time is often required to maintain signal quality. The issue of radiation dose becomes more sever in coherent scattering X-ray tomography, in which the scattering signal is typically orders of magnitude weaker than the transmitted beam. With X-ray photon-counting detectors, transmitted (or scattered) X-ray photons can be acquired at extremely low photon flux, which enables us to greatly reduce the imaging time and dose administrated to the sample. Instead of counting the average the number of photons within a fixed time interval, the arrival times of only a few photons detected in sequence contain sufficient information to estimate the attenuation (or scattering) property, which allows object reconstruction based on our measurement geometry and noise model. We will also discuss compressive or adaptive data acquisition schemes to implement material identification utilizing the energy sensitivity of X-ray photon-counting detector. Our method can be further parallelized with a photon-counting detector array to achieve fast, low-dose X-ray tomographic imaging based on either attenuation or scattering signals, which could find broad applications in medical diagnosis and security screening.

Paper Details

Date Published: 14 May 2018
Proc. SPIE 10632, Anomaly Detection and Imaging with X-Rays (ADIX) III, 106320G (14 May 2018); doi: 10.1117/12.2303981
Show Author Affiliations
Zheyuan Zhu, CREOL, The College of Optics and Photonics, Univ. of Central Florida (United States)
Sean Pang, CREOL, The College of Optics and Photonics, Univ. of Central Florida (United States)

Published in SPIE Proceedings Vol. 10632:
Anomaly Detection and Imaging with X-Rays (ADIX) III
Amit Ashok; Joel A. Greenberg; Michael E. Gehm; Mark A. Neifeld, Editor(s)

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