An Alternating Projection-Image Domains Algorithm for Spectral CT

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An Alternating Projection-Image Domains Algorithm for Spectral CT


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An Alternating Projection-Image Domains Algorithm for Spectral CT

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Spectral computerized tomography (Spectral CT) is a medical and biomedical imaging technique which uses the spectral information of the attenuated X-ray beam. Energy-resolved photon-counting detector is a promising technology for improved spectral CT imaging and allows to obtain material selective images. Two different kind of approaches resolve the problem of spectral reconstruction consisting of material decomposition and tomographic reconstruction: the two-step methods which are most often projection based methods, and the one-step methods. While the projection based methods are interesting for the fast computational time, it is not easy to introduce some spatial priors in the image domain contrary to one-step methods. We present a one-step method combining, in an alternating minimization scheme, a multi-material decomposition in the projection domain and a regularized tomographic reconstruction introducing the spatial priors in the image domain. We present and discuss promising results from experimental data.
Spectral computerized tomography (Spectral CT) is a medical and biomedical imaging technique which uses the spectral information of the attenuated X-ray beam. Energy-resolved photon-counting detector is a promising technology for improved spectral CT imaging and allows to obtain material selective images. Two different kind of approaches resolve the problem of spectral reconstruction consisting of material decomposition and tomographic reconstruction: the two-step methods which are most often projection based methods, and the one-step methods. While the projection based methods are interesting for the fast computational time, it is not easy to introduce some spatial priors in the image domain contrary to one-step methods. We present a one-step method combining, in an alternating minimization scheme, a multi-material decomposition in the projection domain and a regularized tomographic reconstruction introducing the spatial priors in the image domain. We present and discuss promising results from experimental data.