Sundberg C, Danielsson M, Persson M. Compton coincidence in silicon photon-counting CT detectors.
J Med Imaging (Bellingham) 2022;
9:013501. [PMID:
35155716 PMCID:
PMC8823694 DOI:
10.1117/1.jmi.9.1.013501]
[Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 01/03/2022] [Indexed: 11/14/2022] Open
Abstract
Purpose: Compton interactions amount to a significant fraction of the registered counts in a silicon detector. In a Compton interaction, only a part of the photon energy is deposited and a single incident photon can result in multiple counts unless tungsten shielding is used. Deep silicon has proved to be a competitive material for photon-counting CT detectors, but to improve the performance further, one possibility is to use coincidence techniques to identify Compton-scattered photons and reconstruct their incident energies. Approach: In a detector with no tungsten shielding, incident photons can interact through a series of interactions. Based on the position and energy of each interaction, probability-based methods can be used to estimate the incident photon energy. Here, we present a maximum likelihood estimation framework along with an alternative method to estimate the incident photon energy and position in a silicon detector. Results: Assuming one incident photon per time frame, we show that the incident photon energy can be estimated with a mean error of - 0.07 ± 0.03 keV and an RMS error of 3.36 ± 0.02 keV for a realistic case in which we assume a detector with limited energy and spatial resolution. The interaction position was estimated with a mean error of - 2 ± 11 μ m in x direction and 7 ± 11 μ m in y direction. Corresponding RMS errors of 1.09 ± 0.01 and 1.10 ± 0.01 mm were achieved in x and y , respectively. Conclusions: The presented results show the potential of using probability-based methods to improve the performance of silicon detectors for CT.
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