@inproceedings{e12b4f7f293f46b989d20d806c37ac8f,
title = "Component-based TV regularization for X-ray tensor tomography",
abstract = "X-ray Tensor Tomography (XTT) is a recently developed imaging modality that provides reconstruction of X-ray scattering tensors from dark-field projections obtained in a grating interferometry setup. In this work we present a novel component-based total variation (TV) regularized reconstruction technique for XTT data. First results show promising qualitative improvements of the reconstructed tensors as well as reduced noise and reduced streak artifacts.",
keywords = "Computed Tomography, Sparse Regularization, Total Variation, X-ray Tensor Tomography",
author = "Saeed Seyyedi and Matthias Wieczorek and Yash Sharma and Florian Schaff and Christoph Jud and Franz Pfeiffer and Tobias Lasser",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE 13th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 ; Conference date: 13-04-2016 Through 16-04-2016",
year = "2016",
month = jun,
day = "15",
doi = "10.1109/ISBI.2016.7493335",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "581--584",
booktitle = "2016 IEEE International Symposium on Biomedical Imaging",
}