Their effects are shown to be interdependent. In summary, the performance of digital radiography systems depends on the interplay of many sources of image degradation from capture to display. This demonstrates the importance of the choice of display parameters such as those that control grayscale rendering, equalization and edge restoration. 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. Contact to start presenting your products and technologies to an audience of over 100,000 T&D engineers and professionals in more than 180 countries. 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. INMR is ranked as one of the leading site for T&D professionals, with average time on site per session of over 25 minutes. 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. Image quality is quantified in terms of NEQ and DQE. 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. These include technology-dependent sources of image blur and noise.
The image quality of digital radiography systems is influenced by the interplay of many sources of image degradation.
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