Hyperspectral image reconstruction for x-ray fluorescence tomography

摘要: A penalized maximum-likelihood estimation is proposed to perform hyperspectral (spatio-spectral) image reconstruction for X-ray fluorescence tomography. The approach minimizes a Poisson-based negative log-likelihood of the observed photon counts, and uses penalty term that has effect encouraging local continuity model parameter estimates in both spatial spectral dimensions simultaneously. performance method demonstrated with experimental data acquired from seed arabidopsis thaliana collected at 13-ID-E microprobe beamline Advanced Photon Source. resulting element distribution show significantly better quality than conventional analytical inversion approaches, allows high compression factor which can reduce acquisition times remarkably. In particular, this technique provides capability tomographically reconstruct full energy dispersive spectra without compromising artifacts impact interpretation results.