Factors influencing image quality in digital radiographic systems

The image quality of digital radiography systems is influenced by the interplay of many sources of image degradation. These include technology-dependent sources of image blur and noise. This paper systematically investigates the relative influence of the most common sources of image degradation for the entire digital radiography image chain including the detector, image processing and display using well established methods based on linear systems theory. Image quality is quantified in terms of NEQ and DQE. Baseline data are taken from experimental blur and noise measurements from several digital radiography systems, state-of-the-art image processing algorithms and current displays. A generalized theoretical model is exercised to demonstrate the relative importance of the intrinsic noise sources for both direct- and indirect-conversion digital radiography technologies. Since clinical imaging requires a complete system, including a detector, image processing and display, the model is extended to predict the role of image processing and display. This demonstrates the importance of the choice of display parameters such as those that control grayscale rendering, equalization and edge restoration. In summary, the performance of digital radiography systems depends on the interplay of many sources of image degradation from capture to display. Their effects are shown to be interdependent.