TY - JOUR
T1 - Compressive spectral X-ray tomography based on spatial and spectral coded illumination
AU - Cuadros, Angela
AU - Ma, Xu
AU - Arce, Gonzalo R.
N1 - Publisher Copyright:
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
PY - 2019/4/15
Y1 - 2019/4/15
N2 - Spectral computed tomography (CT) relies on the spectral dependence of X-ray attenuation coefficients to separate projection measurements into more than two energy bins. Such data can be used to unveil tomographic material characterization — key in national security and medical imaging. This paper explores a radical departure from conventional methods used in spectral imaging. It relies on K-edge coded apertures to create spatially and spectrally coded, lower-dose, X-ray bundles that interrogate specific voxels of the object. The new approach referred to as compressive spectral X-ray imaging (CSXI) uses low-cost standard X-ray integrating detectors and acquires compressive measurements, which enable the reconstruction of energy binned images from fewer measurements. Various spectral and spatial coding strategies for structured illumination are explored. Subsampling in CSXI is accomplished by either view angle spectral subsampling, spatial subsampling enabled by block-unblock coded apertures placed at the source or detector side, or both. The careful design of subsampling strategies, spectral filters, coded apertures, and their placement, are shown to be critical for the quality of tomographic image reconstruction. The forward imaging model of CSXI, which is a non-linear ill-posed problem, is analyzed and a multi-stage algorithm is developed to address the estimation of the energy binned sinograms from the integrating detector measurements. Then, an Alternating Direction Method of Multipliers (ADMM) is used to solve a joint sparse and low-rank optimization problem for reconstruction that exploits the structure of the spectral X-ray data cube.
AB - Spectral computed tomography (CT) relies on the spectral dependence of X-ray attenuation coefficients to separate projection measurements into more than two energy bins. Such data can be used to unveil tomographic material characterization — key in national security and medical imaging. This paper explores a radical departure from conventional methods used in spectral imaging. It relies on K-edge coded apertures to create spatially and spectrally coded, lower-dose, X-ray bundles that interrogate specific voxels of the object. The new approach referred to as compressive spectral X-ray imaging (CSXI) uses low-cost standard X-ray integrating detectors and acquires compressive measurements, which enable the reconstruction of energy binned images from fewer measurements. Various spectral and spatial coding strategies for structured illumination are explored. Subsampling in CSXI is accomplished by either view angle spectral subsampling, spatial subsampling enabled by block-unblock coded apertures placed at the source or detector side, or both. The careful design of subsampling strategies, spectral filters, coded apertures, and their placement, are shown to be critical for the quality of tomographic image reconstruction. The forward imaging model of CSXI, which is a non-linear ill-posed problem, is analyzed and a multi-stage algorithm is developed to address the estimation of the energy binned sinograms from the integrating detector measurements. Then, an Alternating Direction Method of Multipliers (ADMM) is used to solve a joint sparse and low-rank optimization problem for reconstruction that exploits the structure of the spectral X-ray data cube.
UR - http://www.scopus.com/inward/record.url?scp=85064443359&partnerID=8YFLogxK
U2 - 10.1364/OE.27.010745
DO - 10.1364/OE.27.010745
M3 - Article
C2 - 31052928
AN - SCOPUS:85064443359
SN - 1094-4087
VL - 27
SP - 10745
EP - 10764
JO - Optics Express
JF - Optics Express
IS - 8
ER -