X-ray Tensor Tomography (XTT) is a novel imaging modality for reconstruction of three-dimensional X-ray scattering tensors from dark-field projections obtained in a grating interferometry setup. In this work we propose a new component-based total variation (TV) regularized conjugate gradient (CG) reconstruction method for XTT data. First results suggest that the proposed method’s convergence rate is comparable to different regularization methods, while the resulting reconstructions show less noise and streak artifacts compared to previous, unregularized method.
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X-ray Tensor Tomography (XTT) is a novel imaging modality for reconstruction of three-dimensional X-ray scattering tensors from dark-field projections obtained in a grating interferometry setup. In this work we propose a new component-based total variation (TV) regularized conjugate gradient (CG) reconstruction method for XTT data. First results suggest that the proposed method’s convergence rate is comparable to different regularization methods, while the resulting reconstructions show less n...
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