Signal, noise power spectrum, and detective quantum efficiency of indirect-detection flat-panel imagers for diagnostic radiology.

The performance of an indirect-detection, active matrix flat-panel imager (FPI) at diagnostic energies is reported in terms of measured and theoretical signal size, noise power spectrum (NPS), and detective quantum efficiency (DQE). Based upon a 1536 x 1920 pixel, 127 microns pitch array of a-Si:H thin-film transistors and photodiodes, the FPI was developed as a prototype for examination of the potential of flat-panel technology in diagnostic x-ray imaging. The signal size per unit exposure (x-ray sensitivity) was measured for the FPI incorporating five commercially available Gd2O2S:Tb converting screens at energies 70-120 kVp. One-dimensional and two-dimensional NPS and DQE were measured for the FPI incorporating three such converters and as a function of the incident exposure. The measurements support the hypothesis that FPIs have significant potential for application in diagnostic radiology. A cascaded systems model that has shown good agreement with measured individual pixel signal and noise properties is employed to describe the performance of various FPI designs and configurations under a variety of diagnostic imaging conditions. Theoretical x-ray sensitivity, NPS, and DQE are compared to empirical results, and good agreement is observed in each case. The model is used to describe the potential performance of FPIs incorporating a recently developed, enhanced array that is commercially available and has been proposed for testing and application in diagnostic radiography and fluoroscopy. Under conditions corresponding to chest radiography, the analysis suggests that such systems can potentially meet or even exceed the DQE performance of existing technology, such as screen-film and storage phosphor systems; however, under conditions corresponding to general fluoroscopy, the typical exposure per frame is such that the DQE is limited by the total system gain and additive electronic noise. The cascaded systems analysis provides a valuable means of identifying the limiting stages of the imaging system, a tool for system optimization, and a guide for developing strategies of FPI design for various imaging applications.