A novel quantitative measure of image quality in fluoroscopy

Assessment of fluoroscopic image quality has not kept pace with technological developments in interventional imaging equipment. Access to 'for presentation' data on these systems has motivated this investigation into a novel quantitative method of measuring image quality. We have developed a statistical algorithm as an alternative to subjective assessment using threshold contrast detail detectability techniques. Using sets of uniformity exposed fluoroscopy frames, the algorithm estimates the minimum contrast necessary for conspicuity of a range of virtual target object areas A. Pixel mean value distributions in a central image region are Gaussian, with standard deviation σ Pixel binning produces background distributions with area A. For 95% confidence of conspicuity a target object must exhibit a minimum contrast of 3.29σ. A range of threshold contrasts are calculated for a range of virtual areas. Analysis on a few seconds of fluoroscopy data is performed remotely and no test object is required. In this study Threshold Index and Contrast Detail curves were calculated for different incident air kerma rates at the detector, different levels of electronic magnification and different types of image processing. A limited number of direct comparisons were made with subjective assessments using the Leeds TO.10 test object. Results obtained indicate that the statistical algorithm is not only more sensitive to changes in levels of detector dose rate and magnification, but also to levels of image processing, including edge-enhancement. Threshold Index curves thus produced could be used as an interventional system optimisation tool and to objectively compare image quality between vendor systems.