Component-based TV regularization for X-ray tensor tomography

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

doi:10.1109/ISBI.2016.7493335

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 proceeding › Conference Paper › Research › peer-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 language	English
Title of host publication	2016 IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2016 - Proceedings
Editors	Boudewijn Lelieveldt, Karl Rohr
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	581-584
Number of pages	4
Volume	2016-June
ISBN (Electronic)	9781479923502
DOIs	https://doi.org/10.1109/ISBI.2016.7493335
Publication status	Published - 15 Jun 2016
Externally published	Yes
Event	IEEE International Symposium on Biomedical Imaging (ISBI) 2016 - Clarion Congress Hotel, Prague, Czechia Duration: 13 Apr 2016 → 16 Apr 2016 Conference number: 13th https://ieeexplore.ieee.org/xpl/conhome/7486633/proceeding (Proceedings)

Conference

Conference	IEEE International Symposium on Biomedical Imaging (ISBI) 2016
Abbreviated title	ISBI 2016
Country/Territory	Czechia
City	Prague
Period	13/04/16 → 16/04/16
Other	The 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.
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7486633/proceeding (Proceedings)

Keywords

Computed Tomography
Sparse Regularization
Total Variation
X-ray Tensor Tomography

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10.1109/ISBI.2016.7493335

Cite this

Seyyedi, S., Wieczorek, M., Sharma, Y., Schaff, F., Jud, C., Pfeiffer, F., & Lasser, T. (2016). Component-based TV regularization for X-ray tensor tomography. In B. Lelieveldt, & K. Rohr (Eds.), 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings (Vol. 2016-June, pp. 581-584). Article 7493335 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISBI.2016.7493335

Seyyedi, Saeed ; Wieczorek, Matthias ; Sharma, Yash et al. / Component-based TV regularization for X-ray tensor tomography. 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. editor / Boudewijn Lelieveldt ; Karl Rohr. Vol. 2016-June Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2016. pp. 581-584

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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",

year = "2016",

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doi = "10.1109/ISBI.2016.7493335",

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booktitle = "2016 IEEE International Symposium on Biomedical Imaging",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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note = "IEEE International Symposium on Biomedical Imaging (ISBI) 2016, ISBI 2016 ; Conference date: 13-04-2016 Through 16-04-2016",

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Seyyedi, S, Wieczorek, M, Sharma, Y, Schaff, F, Jud, C, Pfeiffer, F & Lasser, T 2016, Component-based TV regularization for X-ray tensor tomography. in B Lelieveldt & K Rohr (eds), 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. vol. 2016-June, 7493335, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 581-584, IEEE International Symposium on Biomedical Imaging (ISBI) 2016, Prague, Czechia, 13/04/16. https://doi.org/10.1109/ISBI.2016.7493335

Component-based TV regularization for X-ray tensor tomography. / Seyyedi, Saeed; Wieczorek, Matthias; Sharma, Yash et al.
2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. ed. / Boudewijn Lelieveldt; Karl Rohr. Vol. 2016-June Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2016. p. 581-584 7493335.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Component-based TV regularization for X-ray tensor tomography

AU - Seyyedi, Saeed

AU - Wieczorek, Matthias

AU - Sharma, Yash

AU - Schaff, Florian

AU - Jud, Christoph

AU - Pfeiffer, Franz

AU - Lasser, Tobias

N1 - Conference code: 13th

PY - 2016/6/15

Y1 - 2016/6/15

N2 - 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.

AB - 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.

KW - Computed Tomography

KW - Sparse Regularization

KW - Total Variation

KW - X-ray Tensor Tomography

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U2 - 10.1109/ISBI.2016.7493335

DO - 10.1109/ISBI.2016.7493335

M3 - Conference Paper

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BT - 2016 IEEE International Symposium on Biomedical Imaging

A2 - Lelieveldt, Boudewijn

A2 - Rohr, Karl

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - IEEE International Symposium on Biomedical Imaging (ISBI) 2016

Y2 - 13 April 2016 through 16 April 2016

ER -

Seyyedi S, Wieczorek M, Sharma Y, Schaff F, Jud C, Pfeiffer F et al. Component-based TV regularization for X-ray tensor tomography. In Lelieveldt B, Rohr K, editors, 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings. Vol. 2016-June. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2016. p. 581-584. 7493335 doi: 10.1109/ISBI.2016.7493335

Component-based TV regularization for X-ray tensor tomography

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Keywords

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