Image-domain Material Decomposition Based on Spectra Recovery in Spectral CT with Photon-counting Detectors

Abstract

Spectral CT systems based on photon-counting detectors (PCDs) are showing multiple advantages and potentials in medical imaging applications because of their abilities of high energy discrimination capability. For these applications, obtaining incident spectra without distortion is always an important but difficult requirement since the discrimination capability directly depends on the accuracy of the attenuation coefficients obtained. Subject to the influence of charge sharing and photon escaping effects, spectra distortion is unavoidable for PCDs. Moreover, these spectra distortion affects the accuracy of the material decomposition of spectral CT. In this paper, we propose an image-domain material decomposition method based on spectra recovery that consists of two steps. The first step is modeling the detector energy response based on X-ray fluorescence (XRF), and then solving the reverse problem of detector response, with which the distortion-free spectra in the form of energy bins are recovered. Then, the spectral CT image reconstruction and materials decomposition can be done from the recovered data. In the experiments, image-domain material decomposition of four-material phantom (water, calcium, iodine and gadolinium) was conducted, using equivalent attenuation coefficients of each energy bin of the four materials, which is calculated by simulation with standard attenuation coefficients. The comparison of results between those with and without spectra recovery indicates that the failed decomposition due to spectra distortion are effectively corrected by the proposed antidistortion method.