Abstract

4D computed tomography (4D-CT) aims to visualise the temporal dynamics of a 3D sample with a sufficiently high temporal and spatial resolution. Successive time frames are typically obtained by sequential scanning, followed by independent reconstruction of each 3D dataset. Such an approach requires a large number of projections for each scan to obtain images with sufficient quality (in terms of artefacts and SNR). Hence, there is a clear trade-off between the rotation speed of the gantry (i.e. time resolution) and the quality of the reconstructed images. In this paper, the MotionVector-based Iterative Technique (MoVIT) is introduced which reconstructs a particular time frame by including the projections of neighbouring time frames as well. It is shown that such a strategy improves the trade-off between the rotation speed and the SNR. The framework is tested on both numerical simulations and on 4D X-ray CT datasets of polyurethane foam under compression. Results show that reconstructions obtained with MoVIT have a significantly higher SNR compared to the SNR of conventional 4D reconstructions.

© 2017 Optical Society of America

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    [Crossref]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref] [PubMed]
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    [Crossref]
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    [Crossref]
  29. M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
    [Crossref]

2017 (1)

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

2016 (2)

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

W. Van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, and J. Sijbers, “Fast and flexible X-ray tomography using the ASTRA toolbox,” Opt. Express 24, 25129–25147 (2016).
[Crossref] [PubMed]

2015 (3)

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

2014 (4)

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, and J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT,” IEEE Trans. Image Process. 23, 909–919 (2014).
[Crossref] [PubMed]

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

2013 (1)

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

2012 (1)

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

2011 (4)

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

A. Kaestner, B. Münch, P. Trtik, and L. Butler, “Spatiotemporal computed tomography of dynamic processes,” Opt. Eng. 50, 123201 (2011).
[Crossref]

W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics essing units (GPUs),” J. Struct. Biol. 176, 250–253 (2011).
[Crossref] [PubMed]

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

2010 (1)

A. A. Isola, M. Grass, and W. J. Niessen, “Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction,” Med. Phys. 37, 1093–1109 (2010).
[Crossref] [PubMed]

2008 (2)

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

J. Gregor and T. Benson, “Computational analysis and improvement of SIRT,” IEEE Trans. Med. Imaging 27, 918–924 (2008).
[Crossref] [PubMed]

2007 (1)

J. Kaipio and E. Somersalo, “Statistical inverse problems: Discretization, model reduction and inverse crime,” J. Comput. Appl. Math. 198, 493–504 (2007).
[Crossref]

2004 (1)

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

2002 (1)

J. Elliott, A. Windle, and J. Hobdell, “In-situ deformation of an open-cell flexible polyurethane foam characterised by 3D computed microtomography,” J. Mater. Sci. 37, 1547–1555 (2002).
[Crossref]

1999 (2)

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

1984 (1)

Amini, A. A.

M. Negahdar and A. A. Amini, “Estimation of affine motion from projection data using a mass conservation model,” in Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE, 2011), pp. 8041–8044.

Aritan, S.

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

Batenburg, K. J.

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, and J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT,” IEEE Trans. Image Process. 23, 909–919 (2014).
[Crossref] [PubMed]

W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics essing units (GPUs),” J. Struct. Biol. 176, 250–253 (2011).
[Crossref] [PubMed]

W. J. Palenstijn, J. Bédorf, and K. J. Batenburg, “A distributed SIRT implementation for the ASTRA toolbox,” in Proceedings Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2015), pp. 166–169.

Bay, B. K.

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

Bédorf, J.

W. J. Palenstijn, J. Bédorf, and K. J. Batenburg, “A distributed SIRT implementation for the ASTRA toolbox,” in Proceedings Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2015), pp. 166–169.

Benson, T.

J. Gregor and T. Benson, “Computational analysis and improvement of SIRT,” IEEE Trans. Med. Imaging 27, 918–924 (2008).
[Crossref] [PubMed]

Bleichrodt, F.

Bouman, C. A.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Bovik, A. C.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

Brehm, M.

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

Butler, L.

A. Kaestner, B. Münch, P. Trtik, and L. Butler, “Spatiotemporal computed tomography of dynamic processes,” Opt. Eng. 50, 123201 (2011).
[Crossref]

Cant, J.

Cervino, L.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Chen, M.

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

Chen, Q.

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

Christoffersen, C. P. V.

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

Cnudde, V.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Dabravolski, A.

Davis, L. C.

De Beenhouwer, J.

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

W. Van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, and J. Sijbers, “Fast and flexible X-ray tomography using the ASTRA toolbox,” Opt. Express 24, 25129–25147 (2016).
[Crossref] [PubMed]

De Graef, M.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

De Schryver, T.

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

Dierick, M.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Dobson, K. J.

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Elliott, J.

J. Elliott, A. Windle, and J. Hobdell, “In-situ deformation of an open-cell flexible polyurethane foam characterised by 3D computed microtomography,” J. Mater. Sci. 37, 1547–1555 (2002).
[Crossref]

Etchin, S.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Fahey, K.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Feldkamp, L. A.

Folkerts, M.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Frysch, R.

R. Frysch and G. Rose, “Rigid motion compensation in interventional C-arm CT using consistency measure on projection data,” in Proceedings International Conference on Medical Image Computing and Computer-Assisted Intervention (Springer International Publishing, 2015), pp. 298–306.

Fyhrie, D. P.

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

Gibbs, J. W.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Grass, M.

A. A. Isola, M. Grass, and W. J. Niessen, “Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction,” Med. Phys. 37, 1093–1109 (2010).
[Crossref] [PubMed]

Gregor, J.

J. Gregor and T. Benson, “Computational analysis and improvement of SIRT,” IEEE Trans. Med. Imaging 27, 918–924 (2008).
[Crossref] [PubMed]

Gulsoy, E. B.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Hansen, D.

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

Hawkes, D. J.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Hayes, C.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Hill, D. L. G.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Ho, S. P.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Hobdell, J.

J. Elliott, A. Windle, and J. Hobdell, “In-situ deformation of an open-cell flexible polyurethane foam characterised by 3D computed microtomography,” J. Mater. Sci. 37, 1547–1555 (2002).
[Crossref]

Isola, A. A.

A. A. Isola, M. Grass, and W. J. Niessen, “Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction,” Med. Phys. 37, 1093–1109 (2010).
[Crossref] [PubMed]

Jang, A. T.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Janssens, E.

Jia, X.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Jiang, S. B.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Kachelrieß, M.

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

Kaestner, A.

A. Kaestner, B. Münch, P. Trtik, and L. Butler, “Spatiotemporal computed tomography of dynamic processes,” Opt. Eng. 50, 123201 (2011).
[Crossref]

Kaestner, A. P.

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Kaipio, J.

J. Kaipio and E. Somersalo, “Statistical inverse problems: Discretization, model reduction and inverse crime,” J. Comput. Appl. Math. 198, 493–504 (2007).
[Crossref]

Kazantsev, D.

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

Kingston, A. M.

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Koksel, F.

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

Kress, J. W.

Kunz, P.

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

Ladikos, A.

W. Wein and A. Ladikos, “Towards general motion recovery in cone-beam computed tomography,” in Proceedings of Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2013), pp. 54–57.

Leach, M. O.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Lee, P. D.

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Li, Y.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Lin, J. D.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Lionheart, W. R. B.

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Lu, W.

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

Masschaele, B.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Merkle, A.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Mohan, K. A.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Mou, X.

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

Münch, B.

A. Kaestner, B. Münch, P. Trtik, and L. Butler, “Spatiotemporal computed tomography of dynamic processes,” Opt. Eng. 50, 123201 (2011).
[Crossref]

Myers, G. R.

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Negahdar, M.

M. Negahdar and A. A. Amini, “Estimation of affine motion from projection data using a mass conservation model,” in Proceedings of Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE, 2011), pp. 8041–8044.

Niessen, W. J.

A. A. Isola, M. Grass, and W. J. Niessen, “Fully automatic nonrigid registration-based local motion estimation for motion-corrected iterative cardiac CT reconstruction,” Med. Phys. 37, 1093–1109 (2010).
[Crossref] [PubMed]

Oelhafen, M.

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

Olivera, G. H.

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

Page, J. H.

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

Palenstijn, W. J.

W. Van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, and J. Sijbers, “Fast and flexible X-ray tomography using the ASTRA toolbox,” Opt. Express 24, 25129–25147 (2016).
[Crossref] [PubMed]

W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics essing units (GPUs),” J. Struct. Biol. 176, 250–253 (2011).
[Crossref] [PubMed]

W. J. Palenstijn, J. Bédorf, and K. J. Batenburg, “A distributed SIRT implementation for the ASTRA toolbox,” in Proceedings Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2015), pp. 166–169.

Pan, T.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Paysan, P.

M. Brehm, P. Paysan, M. Oelhafen, P. Kunz, and M. Kachelrieß, “Self-adapting cyclic registration for motion-compensated cone-beam CT in image-guided radiation therapy,” Med. Phys. 39, 7603–7618 (2012).
[Crossref] [PubMed]

Poulsen, P.

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

Rose, G.

R. Frysch and G. Rose, “Rigid motion compensation in interventional C-arm CT using consistency measure on projection data,” in Proceedings International Conference on Medical Image Computing and Computer-Assisted Intervention (Springer International Publishing, 2015), pp. 298–306.

Ruchala, K. J.

M. Chen, W. Lu, Q. Chen, K. J. Ruchala, and G. H. Olivera, “A simple fixed-point approach to invert a deformation field,” Med. Phys. 35, 81–88 (2008).
[Crossref] [PubMed]

Rueckert, D.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Saad, M.

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

Scanlon, M. G.

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

Seo, Y.

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Sheikh, H. R.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

Sheppard, A. P.

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Sijbers, J.

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

W. Van Aarle, W. J. Palenstijn, J. Cant, E. Janssens, F. Bleichrodt, A. Dabravolski, J. De Beenhouwer, and J. Sijbers, “Fast and flexible X-ray tomography using the ASTRA toolbox,” Opt. Express 24, 25129–25147 (2016).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, and J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT,” IEEE Trans. Image Process. 23, 909–919 (2014).
[Crossref] [PubMed]

W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics essing units (GPUs),” J. Struct. Biol. 176, 250–253 (2011).
[Crossref] [PubMed]

Simoncelli, E. P.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

Smith, T. S.

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

Somersalo, E.

J. Kaipio and E. Somersalo, “Statistical inverse problems: Discretization, model reduction and inverse crime,” J. Comput. Appl. Math. 198, 493–504 (2007).
[Crossref]

Sonoda, L. I.

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Sorensen, T. S.

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

Strybulevych, A.

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

Thompson, W. M.

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Trtik, P.

A. Kaestner, B. Münch, P. Trtik, and L. Butler, “Spatiotemporal computed tomography of dynamic processes,” Opt. Eng. 50, 123201 (2011).
[Crossref]

Turner, M. L.

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Van Aarle, W.

Van Acker, J.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Van den Bulcke, J.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Van Eyndhoven, G.

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

G. Van Eyndhoven, K. J. Batenburg, and J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT,” IEEE Trans. Image Process. 23, 909–919 (2014).
[Crossref] [PubMed]

Van Hoorebeke, L.

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Van Loo, D.

M. Dierick, D. Van Loo, B. Masschaele, J. Van den Bulcke, J. Van Acker, V. Cnudde, and L. Van Hoorebeke, “Recent micro-CT scanner developments at UGCT,” Nucl. Instr. Meth. Phys. Res. B 324, 35–40 (2014).
[Crossref]

Van Nieuwenhove, V.

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

Varslot, T. K.

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Venkatakrishnan, S. V.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Voorhees, P. W.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Wang, Z.

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

Wein, W.

W. Wein and A. Ladikos, “Towards general motion recovery in cone-beam computed tomography,” in Proceedings of Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2013), pp. 54–57.

Windle, A.

J. Elliott, A. Windle, and J. Hobdell, “In-situ deformation of an open-cell flexible polyurethane foam characterised by 3D computed microtomography,” J. Mater. Sci. 37, 1547–1555 (2002).
[Crossref]

Withers, P. J.

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

Xiao, X.

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

Yan, H.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Zhang, D.

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

Zhang, L.

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

Zhen, X.

H. Yan, X. Zhen, M. Folkerts, Y. Li, T. Pan, L. Cervino, S. B. Jiang, and X. Jia, “A hybrid reconstruction algorithm for fast and accurate 4D cone-beam CT imaging,” Med. Phys. 41, 071903 (2014).
[Crossref] [PubMed]

Appl. Opt. (1)

G. R. Myers, A. M. Kingston, T. K. Varslot, M. L. Turner, and A. P. Sheppard, “Dynamic tomography with a priori information,” Appl. Opt. 50, 2685–3690 (2011).
[Crossref]

Exp. Mech. (1)

B. K. Bay, T. S. Smith, D. P. Fyhrie, and M. Saad, “Digital volume correlation: Three-dimensional strain mapping using X-ray tomography,” Exp. Mech. 39, 217–226 (1999).
[Crossref]

Food Res. Int. (1)

F. Koksel, S. Aritan, A. Strybulevych, J. H. Page, and M. G. Scanlon, “The bubble size distribution and its evolution in non-yeasted wheat flour doughs investigated by synchrotron X-ray microtomography,” Food Res. Int. 80, 12–18 (2016).
[Crossref]

IEEE Trans. Comp. Imaging (1)

K. A. Mohan, S. V. Venkatakrishnan, J. W. Gibbs, E. B. Gulsoy, X. Xiao, M. De Graef, P. W. Voorhees, and C. A. Bouman, “TIMBIR: a method for time-space reconstruction from interlaced view,” IEEE Trans. Comp. Imaging 1, 96–111 (2015).
[Crossref]

IEEE Trans. Image Process. (5)

G. Van Eyndhoven, K. J. Batenburg, D. Kazantsev, V. Van Nieuwenhove, P. D. Lee, K. J. Dobson, and J. Sijbers, “An iterative CT reconstruction algorithm for fast fluid flow imaging,” IEEE Trans. Image Process. 24, 4446–4458 (2015).
[Crossref] [PubMed]

G. Van Eyndhoven, K. J. Batenburg, and J. Sijbers, “Region-based iterative reconstruction of structurally changing objects in CT,” IEEE Trans. Image Process. 23, 909–919 (2014).
[Crossref] [PubMed]

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: From error visibility to structural similarity,” IEEE Trans. Image Process. 13, 600–612 (2004).
[Crossref] [PubMed]

L. Zhang, L. Zhang, X. Mou, and D. Zhang, “FSIM : A feature similarity index for image quality assessment,” IEEE Trans. Image Process. 20, 2378–2386 (2011).
[Crossref] [PubMed]

V. Van Nieuwenhove, J. De Beenhouwer, T. De Schryver, L. Van Hoorebeke, and J. Sijbers, “Data-driven affine deformation estimation and correction in cone beam computed tomography,” IEEE Trans. Image Process. 26, 1441–1451 (2017).
[Crossref] [PubMed]

IEEE Trans. Med. Imaging (3)

C. P. V. Christoffersen, D. Hansen, P. Poulsen, and T. S. Sorensen, “Registration-based reconstruction of four-dimensional cone beam computed tomography,” IEEE Trans. Med. Imaging 32, 2064–2077 (2013).
[Crossref] [PubMed]

J. Gregor and T. Benson, “Computational analysis and improvement of SIRT,” IEEE Trans. Med. Imaging 27, 918–924 (2008).
[Crossref] [PubMed]

D. Rueckert, L. I. Sonoda, C. Hayes, D. L. G. Hill, M. O. Leach, and D. J. Hawkes, “Nonrigid registration using free-form deformations: application to breast MR images,” IEEE Trans. Med. Imaging 18, 712–721 (1999).
[Crossref] [PubMed]

Inverse Probl. Imag. (1)

D. Kazantsev, W. M. Thompson, W. R. B. Lionheart, G. Van Eyndhoven, A. P. Kaestner, K. J. Dobson, P. J. Withers, and P. D. Lee, “4D-CT reconstruction with unified spatial-temporal patch-based regularization,” Inverse Probl. Imag. 9, 447–467 (2015).
[Crossref]

J. Comput. Appl. Math. (1)

J. Kaipio and E. Somersalo, “Statistical inverse problems: Discretization, model reduction and inverse crime,” J. Comput. Appl. Math. 198, 493–504 (2007).
[Crossref]

J. Mater. Sci. (1)

J. Elliott, A. Windle, and J. Hobdell, “In-situ deformation of an open-cell flexible polyurethane foam characterised by 3D computed microtomography,” J. Mater. Sci. 37, 1547–1555 (2002).
[Crossref]

J. Opt. Soc. Am. A (1)

J. Struct. Biol. (1)

W. J. Palenstijn, K. J. Batenburg, and J. Sijbers, “Performance improvements for iterative electron tomography reconstruction using graphics essing units (GPUs),” J. Struct. Biol. 176, 250–253 (2011).
[Crossref] [PubMed]

J. Vis. Exp. (1)

A. T. Jang, J. D. Lin, Y. Seo, S. Etchin, A. Merkle, K. Fahey, and S. P. Ho, “In situ compressive loading and correlative noninvasive imaging of the bone-periodontal ligament-tooth fibrous joint,” J. Vis. Exp. 85, 51147 (2014).

Med. Phys. (4)

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Nucl. Instr. Meth. Phys. Res. B (1)

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Opt. Express (1)

Other (4)

W. J. Palenstijn, J. Bédorf, and K. J. Batenburg, “A distributed SIRT implementation for the ASTRA toolbox,” in Proceedings Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2015), pp. 166–169.

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W. Wein and A. Ladikos, “Towards general motion recovery in cone-beam computed tomography,” in Proceedings of Fully Three-Dimensional Image Reconstruction Radiology and Nuclear Medicine (2013), pp. 54–57.

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Figures (9)

Fig. 1
Fig. 1

Illustration of the projection process. The contribution aij of pixel xj to the projection value qi is represented as the ray-intersection length of projection line i with pixel j.

Fig. 2
Fig. 2

Schematic representation of a single iteration of the MoVIT algorithm implemented with SIRT updates.

Fig. 3
Fig. 3

Schematic representation of the full MoVIT reconstruction pipeline.

Fig. 4
Fig. 4

Renderings of the simulated reconstruction of the compression of a foam sample with different (a) FDK, (b) SIRT, (c) FDKmean, (d) SIRTmean, and (e) MoVIT. The red circles indicate example areas where the struts that are better reconstructed in the MoVIT reconstructions in comparison with the SIRTmean reconstruction.

Fig. 5
Fig. 5

MSE, SSIM and FSIM of the reconstructions of the numerical phantoms (see Section 3.3) in function of the photon count I0 and with 20 projections per time frame.

Fig. 6
Fig. 6

MSE, SSIM and FSIM of the reconstructions of the numerical phantoms (see Section 3.3) in function of the projections per time frame and a photon count of 104.

Fig. 7
Fig. 7

The mean MSE (a), SSIM (b) and FSIM (c) for the SIRT (yellow), SIRTmean (purple) and MoVIT with 2 time frames (green) reconstruction with 1000 proj/time frame (compared with the SIRT reconstruction with 2000 proj/time frame) for each time frame. The standard deviation of the metrics was determined by calculating the metrics on 100 horizontal cross sections. (d) shows the histogram of the region displayed in Fig. 8 for the different reconstructions of the third time frame.

Fig. 8
Fig. 8

Zoomed horizontal cross section through the third time frame of the polyurethane dataset.

Fig. 9
Fig. 9

Vertical cross section through the third time frame of the polyurethane dataset.

Tables (2)

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Algorithm 1. Basic steps of the MoVIT algorithm

Tables Icon

Table 1 Standard Deviation of the Noise

Equations (10)

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x k = x k 1 + CA T R ( p Ax k 1 )
[ A 1 0 0 0 A 2 0 0 0 A R ] = [ x 1 x 2 x R ] = A ˜ x ˜ = p ˜ ,
x r = τ r r x r
A ˜ x ˜ = A ˜ [ x 1 x R ] = A ˜ [ τ r 1 τ r R ] x r
𝒜 r x r = p ˜
𝒜 r = [ A 1 τ r 1 A R τ r R ] ,
x r k + 1 = x r k + r 𝒩 r w r r τ r r 1 C r A r T R r ( p r A r τ r r x r k )
μ r r = argmin μ ( 1 N i = 1 N ( c r , i ( τ ( μ ) c r ) i ) 2 )
w r r = exp ( ( k r r / b ) 2 ) l 𝒩 r exp ( ( k r l / b ) 2 )
α r r = argmin α ( 1 N i = 1 N ( f r , i ( τ ( α ) f r ) i ) 2 )

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