Component-based TV regularization for X-ray tensor tomography

Saeed Seyyedi, Matthias Wieczorek, Yash Sharma, Florian Schaff, Christoph Jud, Franz Pfeiffer, Tobias Lasser

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publication2016 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2016 - Proceedings
EditorsBoudewijn Lelieveldt, Karl Rohr
Place of PublicationPiscataway NJ USA
PublisherIEEE Computer Society
Pages581-584
Number of pages4
Volume2016-June
ISBN (Electronic)9781479923502
DOIs
Publication statusPublished - 15 Jun 2016
Externally publishedYes
EventIEEE International Symposium on Biomedical Imaging (ISBI) 2016 - Clarion Congress Hotel, Prague, Czech Republic
Duration: 13 Apr 201616 Apr 2016
Conference number: 13th

Conference

ConferenceIEEE International Symposium on Biomedical Imaging (ISBI) 2016
Abbreviated titleISBI 2016
CountryCzech Republic
CityPrague
Period13/04/1616/04/16
OtherThe ISBI conference has been organized since 2002 and it continues to fulfill its role of bringing together researchers from the various fields that comprise biomedical imaging, such as biology, medicine,imaging technology, image processing, machine learning and many others.

Keywords

  • Computed Tomography
  • Sparse Regularization
  • Total Variation
  • X-ray Tensor Tomography

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