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Four-dimensional tomographic reconstruction by time domain decomposition

Carlsson, Marcus LU ; Andersson, Fredrik LU ; Nikitin, Viktor LU and Mokso, Rajmund LU (2019) In IEEE Transactions on Computational Imaging 5(3). p.409-419
Abstract
For classical tomography, it is essential that the sample does not change during the acquisition of one tomographic rotation. We derived and successfully implemented a tomographic reconstruction method, which relaxes this requirement of quasistatic samples. In the present paper, dynamic tomographic data sets are decomposed in the temporal domain by projecting to a lower dimensional subspace of basis functions and deploying an additional L1 regularization technique where the penalty factor is taken for spatial and temporal derivatives. We adopted the primal-dual algorithm of Chambolle and Pock for solving the projected regularization problem and tested it on synthetic data containing different motion types. The proposed implementation on... (More)
For classical tomography, it is essential that the sample does not change during the acquisition of one tomographic rotation. We derived and successfully implemented a tomographic reconstruction method, which relaxes this requirement of quasistatic samples. In the present paper, dynamic tomographic data sets are decomposed in the temporal domain by projecting to a lower dimensional subspace of basis functions and deploying an additional L1 regularization technique where the penalty factor is taken for spatial and temporal derivatives. We adopted the primal-dual algorithm of Chambolle and Pock for solving the projected regularization problem and tested it on synthetic data containing different motion types. The proposed implementation on modern GPU systems demonstrates the applicability of the method for processing real data sets. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
IEEE Transactions on Computational Imaging
volume
5
issue
3
pages
409 - 419
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
ISSN
2333-9403
DOI
10.1109/TCI.2019.2898088
language
English
LU publication?
yes
id
9143f15f-1ffe-4b88-95f5-ed9a7cdb6694
date added to LUP
2020-05-11 11:17:37
date last changed
2020-05-11 22:03:30
@article{9143f15f-1ffe-4b88-95f5-ed9a7cdb6694,
  abstract     = {{For classical tomography, it is essential that the sample does not change during the acquisition of one tomographic rotation. We derived and successfully implemented a tomographic reconstruction method, which relaxes this requirement of quasistatic samples. In the present paper, dynamic tomographic data sets are decomposed in the temporal domain by projecting to a lower dimensional subspace of basis functions and deploying an additional L1 regularization technique where the penalty factor is taken for spatial and temporal derivatives. We adopted the primal-dual algorithm of Chambolle and Pock for solving the projected regularization problem and tested it on synthetic data containing different motion types. The proposed implementation on modern GPU systems demonstrates the applicability of the method for processing real data sets.}},
  author       = {{Carlsson, Marcus and Andersson, Fredrik and Nikitin, Viktor and Mokso, Rajmund}},
  issn         = {{2333-9403}},
  language     = {{eng}},
  number       = {{3}},
  pages        = {{409--419}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  series       = {{IEEE Transactions on Computational Imaging}},
  title        = {{Four-dimensional tomographic reconstruction by time domain decomposition}},
  url          = {{http://dx.doi.org/10.1109/TCI.2019.2898088}},
  doi          = {{10.1109/TCI.2019.2898088}},
  volume       = {{5}},
  year         = {{2019}},
}