4.3 Article

Contaminant detection in non-destructive testing using a CZT photon-counting detector

Journal

JOURNAL OF INSTRUMENTATION
Volume 16, Issue 1, Pages -

Publisher

IOP PUBLISHING LTD
DOI: 10.1088/1748-0221/16/01/P01011

Keywords

Inspection with x-rays; X-ray detectors

Funding

  1. Natural Sciences and Engineering Research Council of Canada (NSERC)
  2. Canada Research Chair program

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The recent advancements in CdZnTe (CZT) sensors have led to increased commercial use of high-flux photon-counting detectors (PCDs) in non-destructive testing (NDT), particularly in applications such as food inspection. By analyzing pulse height and sorting x-rays into energy bins, PCDs offer better detection capabilities than traditional radiography. Parameters such as energy thresholds and pixel binning schemes can optimize contaminant detectability in x-ray images.
With recent advances in the growth of CdZnTe (CZT) sensors, high-flux photon-counting detectors (PCDs) have begun to see more use commercially in non-destructive testing (NDT). One such application is food inspection, where radiography is currently used to detect undesirable contaminants introduced in the production and packaging processes. PCDs can offer better detection than conventional radiography due to the preservation of energy data by analyzing the pulse height of each x-ray detection and sorting the x-ray into one of a number of energy bins. However, there are a number of parameters that must be explored in order to offer efficient and efficacious detection of contaminants. Here, two such parameters were investigated in a phantom study with an 8x24 mm 2 CZT detector for a number of common contaminant materials. The detectability of contaminants was evaluated based on their contrast-to-noise ratio (CNR) in 2D transmission images. First, the energy bin demonstrating the highest CNR for each contaminant material was found by adjusting the threshold energies defining the edges of the bin. Second, various pixel binning schemes were utilized to lower noise and investigate the effect on the detectability based on the size of contaminants. CNR was maximized for pixel binning that corresponded to the approximate size of the contaminant objects in x-ray images.

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