Resolution-enhancing hybrid, spectral CT reconstruction

Abstract

Spectral x-ray imaging based on photon-counting x-ray detectors (PCXD) is an area of growing interest. By measuring the energy of x-ray photons, a spectral CT system can better differentiate elements using a single scan. However, the spatial resolution achievable with most PCXDs limits their application, particularly in preclinical CT imaging. Consequently, our group is developing a hybrid micro-CT scanner based on a high-resolution, energy-integrating (EID) detector and a lower-resolution, PCXD. To complement this system, we propose and demonstrate a hybrid, spectral CT reconstruction algorithm which robustly combines the spectral contrast of the PCXD with the spatial resolution of the EID. Specifically, the high-resolution, spectrally resolved data (X) is recovered as the sum of two matrices: one with low column rank (X L ) determined from the EID data and one with intensity gradient sparse columns (X S ) corresponding to the upsampled spectral contrast obtained from the PCXD data. We test the proposed algorithm in a feasibility study focused on molecular imaging of atherosclerotic plaque using activatable iodine and gold nanoparticles. The results show accurate estimation of material concentrations at increased spatial resolution for a voxel size ratio between the PCXD and the EID of 500 µm 3 :100 µm 3 . Specifically, regularized, iterative reconstruction of the MOBY mouse phantom around the K-edges of iodine (33.2 keV) and gold (80.7 keV) reduces the reconstruction error by more than a factor of three relative to least-squares, algebraic reconstruction. Likewise, the material decomposition accuracy into iodine, gold, calcium, and water improves by more than a factor of two.