A novel quantitative measure of image quality in fluoroscopy

Abstract

The aim of this work is to develop a quantitative algorithm for the assessment of image quality in fluoroscopy as an alternative to the subjective Leeds Test Object TO-10. Current possible quantitative measurements such as Detective Quantum Efficiency and Modulation Transfer Function do not assess the effects of imaging processing, such as edge-enhancement and noise reduction, on the final displayed image. A standard statistical algorithm used to calculate the contrast needed to observe an object having area size (A) against background. The algorithm was developed to produce sets of Contrast-Detail and Threshold Contrast curves. Three flat panel fluoroscopy systems in our Cardiology were examined. Sequences of uniform fluoroscopy images, obtained using 1 mm of copper as an attenuator, were acquired and then analysed remotely. For each system curves were generated for (a) different dose rates at the detector, (b) different settings of magnification, & (c) different levels of edge-enhancement. For one system different levels of noise reduction were examined. Areas under contrast-detail and threshold-contrast curves reflect changes in dose rate at the detector. The algorithm is sensitive to changes in applied edge-enhancement and noise reduction. Both sets of curves for each system exhibit characteristic spatial frequency responses. This new efficient and objective algorithm measures fluoroscopic image quality using the standard Threshold Detection Index. It tracks quality changes that depend not only on input dose rate, but also the level of image processing applied. It only requires the acquisition of a few seconds of fluoroscopy to produce images for remote analysis.