A theoretical investigation of factors limiting the detective quantum efficiency (DQE) of active matrix flat-panel imagers (AMFPIs), and of methods to overcome these limitations, is reported. At the higher exposure levels associated with radiography, the present generation of AMFPIs is capable of exhibiting DQE performance equivalent, or superior, to that of existing film-screen and computed radiography systems. However, at exposure levels commonly encountered in fluoroscopy, AMFPIs exhibit significantly reduced DQE and this problem is accentuated at higher spatial frequencies. The problem applies both to AMFPIs that rely on indirect detection as well as direct detection of the incident radiation. This reduced performance derives from the relatively large magnitude of the square of the total additive noise compared to the system gain for existing AMFPIs. In order to circumvent these restrictions, a variety of strategies to decrease additive noise and enhance system gain are proposed. Additive noise could be reduced through improved preamplifier, pixel and array design, including the incorporation of compensation lines to sample external line noise. System gain could be enhanced through the use of continuous photodiodes, pixel amplifiers, or higher gain x-ray converters such as lead iodide. The feasibility of these and other strategies is discussed and potential improvements to DQE performance are quantified through a theoretical investigation of a variety of hypothetical 200 μm pitch designs. At low exposures, such improvements could greatly increase the magnitude of the low spatial frequency component of the DQE, rendering it practically independent of exposure while simultaneously reducing the falloff in DQE at higher spatial frequencies. Furthermore, such noise reduction and gain enhancement could lead to the development of AMFPIs with high DQE performance which are capable of providing both high resolution radiographic images, at ∼100 μm pixel resolution, as well as variable resolution fluoroscopic images at 30 fps.