Cascaded System Analysis of a Direct-indirect Dual-layer Flat-panel-detector for Contrast-enhanced Breast Imaging

A direct-indirect dual-layer flat-panel-detector (DI-DLFPD) was recently proposed to mitigate motion artifacts in dual-energy (DE) breast imaging. In this work, we developed a cascaded linear system model to predict the imaging performance of the DI-DLFPD and applied it to the lesion detection task in contrast-enhanced digital mammography. CsI scintillator was used in the back layer (BL) detector to acquire high-energy (HE) images, and the random variations of optical gain and blur in CsI were considered in noise propagation. The optical parameters were estimated from single x-ray imaging results previously obtained by our lab. Pre-sampling modular transfer function and normalized noise power spectrum in low-energy and HE images were modeled to derive spatial-frequency-dependent signal and noise in DE images. The detectability index (d') of iodinated objects was calculated as a function of the thicknesses of the Ag filter, front layer (FL) a-Se detector, and BL CsI scintillator. Reasonable agreement between modeled performance and measurements demonstrated the feasibility of applying the model to predict imaging performance. The results showed that employing a 100 μm thick Ag filter with a 200 μm thick a-Se in FL and a 400 μm thick CsI in BL yields d' close to the optimum for this task. In the future, we will extend this model to more tasks like microcalcification detection to guide the optimization of the DI-DLFPD breast imaging system design.