Contaminant detection using a CZT photon counting detector with TDI image reconstruction
Joanna Nguyen, Devon Richtsmeier, Kris Iniewski, Magdalena, Bazalova-Carter

TL;DR
This study demonstrates that a cadmium zinc telluride photon counting detector can effectively detect physical contaminants in food inspection systems, especially when imaging moving objects, by providing improved contrast-to-noise ratios over stationary imaging.
Contribution
The paper introduces the use of a CZT photon counting detector with TDI image reconstruction for contaminant detection in food inspection, highlighting its effectiveness during conveyor belt movement.
Findings
Moving phantom images have higher contrast-to-noise ratios than stationary images for imaging times over 25 ms.
CZT PCD can detect physical contaminants effectively, surpassing traditional line scan sensors.
Imaging at multiple energy bins enhances contaminant discrimination.
Abstract
Food x-ray inspection systems are designed to detect unwanted physical contaminants in packaged food to maintain a high level of food safety for consumers. Modern day x-ray inspection systems often utilize line scan sensors to detect these physical contaminants but are limited to single or dual energies. However, by using a photon counting detector (PCD), a new generation of food inspection systems capable of acquiring images at more than two energy bins could improve discrimination between low density contaminants. In this work, five type of contaminants were embedded in an acrylic phantom and imaged using a cadmium zinc telluride (CZT) PCD with a pixel pitch of 330 um. A set of images were acquired while the phantom was stationary, and another set of images were acquired while the phantom was moving to mimic the movement of a conveyor belt. Image quality was assessed by evaluating the…
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