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Titel:

Total Variation Regularization for X-Ray Tensor Tomography

Dokumenttyp:
Konferenzbeitrag
Autor(en):
Wieczorek, M.; Vogel, J.; Weinmann, A.; Jud, C.; Schaff, F.; Storath, M.; Pfeiffer, F.; Baust, M.; Lasser, T.
Abstract:
Tensor-valued data is more complex to validly denoise, as these shapes are usually constrained. Considerable efforts have been spent on achieving this for Diffusion Tensor Imaging. A novel tensor-valued imaging modality, X-ray Tensor Tomography (XTT) has recently been presented, where the tensors describe scattering of X-ray beams. In this work, we investigate the applicability of a Total-Variation-based method enforcing the tensors to remain on their manifold.
Stichworte:
CAMP,MedicalImaging,Reconstruction,FULLY3D,XTT,TV
Kongress- / Buchtitel:
Proc. Int'l Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (Fully3D)
Jahr:
2015
 BibTeX