Image Quality in Digital Radiography: First Results of an analytical modeling approach

Abstract

Any X-ray detector for medical imaging needs to serve the purpose of efficiently absorbing the impinging X-ray flux and converting it into a geometryconserving digital image signal. The detector used should be optimized for each X-ray imaging modality. The aim of this work was to develop an analytical model simulating an indirect flat panel digital detector which could be later utilized in Computed Tomography Breast Imaging and to evaluate 2-dimensional images produced by irradiating a software phantom consisting of different orthogonal structures (tumor and microcalcifications). The detector was modeled within the framework of the linear cascaded systems (LCS) theory. The image unsharpness as well as the statistical noise, where post introduced in the final image, by utilizing the Transfer Function and the Noise Power Spectrum derived from the LCS model. Phantom images of various exposures conditions were derived. It was observed that the structures of the phantom were more visible as the kV and tissue thickness increased. Finally the microcalcifications were distinguished more easily than the tumors