ArticleNuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment2019
Image quality assessment of a photon counting detector in x-ray projection imaging.
Article in Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The recent advancements in the photon counting detection have created a significant growing research interest in the x-ray imaging. It is essential to objectively understand the image quality parameters of a photon counting detector before developing imaging applications. In this work, we have assessed the imaging quality of a cadmium telluride (CdTe) based PCD in projection imaging mode. The detector is 70.4 mm × 6.6 mm dimensions. The detector has a pixel array of 64×4 with a pixel pitch of 1.1 mm×1.65 mm. With each pixel having 4 channels in its corresponding ASIC, this PCD can create three bin images from a single projection. With a microfocus x-ray source, the imaging quality in each bin image was measured in terms of the spatial resolution, noise, and contrast to noise ratio (CNR). We used 70 kV, 50μA, 10 s (0.5mAs) with 0.5mm thick aluminum (Al) filter for the acquisition of each image. The MTF curves indicated that the spatial resolution for the bin-1, bin-2, and bin-3 was almost identical. The NNPS curves indicated that the noise in bin 1 and bin 2 images was almost the same for all frequencies while bin 3 image had relatively less noise. The CNR analyses showed that the bin-1 image had the highest CNR. As the flux was increased from 0.5 to 1 mAs, the number of detected counts also increased that resulted in the CNR increase. Beyond this flux, the pulse pileup occurred due to which multiple counts were read as single that resulted in few detected counts and lower CNR. The knowledge of the spatial resolution, noise, and CNR in terms of energy binning allows the determination and optimization of imaging techniques necessary for various applications.
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