Paper
28 May 1999 Algorithm to correct for z-detector gain variations in multislice volumetric CT
Guy M. Besson, Hui Hu, Min Xie, H. David He, Neil Bromberg, George Seidenschnur
Author Affiliations +
Abstract
This paper presents a calibration and correction method for detector cell gain variations. To provide variable slice thickness capability in multislice volumetric scanners, while minimizing costs, it is necessary to combine the signals from several detector cells. The process of combining the output of several detector cells with non-uniform gains can introduce numerical errors when the impinging x-ray signal varies over the range of the combined cells. These scan dependent numerical errors can lead to artifacts in the reconstructed images, particularly when the numerical errors vary from channel-to-channel. A projection data correction algorithm has been developed to subtract the associated numerical errors. For effectiveness and data flow reasons, the algorithm works on a slice-by-slice basis. An initial error vector is calculated by applying a high-pass filter to the projection data. The essence of the algorithm is to correlate that initial error vector, with a calibration vector obtained by applying the same high-pass filter to various z-combinations of the cell gains. The solution to the least-square problem gives the coefficients of a polynomial expansion of the signal z-slope and curvature. From this information, and given the cell gains, the final error vector is calculated and subtracted from the projection data.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guy M. Besson, Hui Hu, Min Xie, H. David He, Neil Bromberg, and George Seidenschnur "Algorithm to correct for z-detector gain variations in multislice volumetric CT", Proc. SPIE 3659, Medical Imaging 1999: Physics of Medical Imaging, (28 May 1999); https://doi.org/10.1117/12.349491
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KEYWORDS
Sensors

Calibration

X-rays

Signal detection

Detection and tracking algorithms

Linear filtering

X-ray computed tomography

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