Optimization of image process parameters through factorial experiments using a flat panel detector

In the optimization process of lumbar spine examinations, factorial experiments were performed addressing the question of whether the effective dose can be reduced and the image quality maintained by adjusting the image processing parameters. A 2k-factorial design was used which is a systematic and effective method of investigating the influence of many parameters on a result variable. Radiographic images of a Contrast Detail phantom were exposed using the default settings of the process parameters for lumbar spine examinations. The image was processed using different settings of the process parameters. The parameters studied were ROI density, gamma, detail contrast enhancement (DCE), noise compensation, unsharp masking and unsharp masking kernel (UMK). The images were computer analysed and an image quality figure (IQF) was calculated and used as a measurement of the image quality. The parameters with the largest influence on image quality were noise compensation, unsharp masking, unsharp masking kernel and detail contrast enhancement. There was an interaction between unsharp masking and kernel indicating that increasing the unsharp masking improved the image quality when combined with a large kernel size. Combined with a small kernel size however the unsharp masking had a deteriorating effect. Performing a factorial experiment gave an overview of how the image quality was influenced by image processing. By adjusting the level of noise compensation, unsharp masking and kernel, the IQF was improved to a 30% lower effective dose.