@conference {1589,
	title = {A 4D CT reconstruction algorithm for fast liquid flow imaging},
	year = {2015},
	abstract = {  The study of fluid flow through solid matter by computed tomography (CT) imaging has a broad range of applications, ranging from oil extraction to scientific research on fluid dynamics. Current techniques are often limited by a low temporal/spatial resolution. In this talk, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flowing through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation of a particular voxel in the dynamic region is modeled by a piecewise constant function over time (i.e., the voxel consists of fluid or air). Experiments on simulation data and on a real neutron tomography dataset demonstrate that the proposed approach can significantly increase the temporal resolution in comparison to conventional algorithms.},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
@article {1570,
	title = {4D-CT reconstruction with unified spatial-temporal patch-based regularization},
	journal = { Inverse Problems and Imaging},
	volume = {9},
	year = {2015},
	pages = {447-467},
	doi = {10.3934/ipi.2015.9.447},
	author = {Kazantsev, Daniil and Thompson, William M. and Lionheart, William R. B. and Van Eyndhoven, Geert and Kaestner,  Anders P. and Katherine J Dobson and Withers, Philip J. and Lee, Peter D.}
}
@article {1579,
	title = {Employing temporal self-similarity across the entire time domain in computed tomography reconstruction},
	journal = {Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences},
	volume = {373},
	number = {2043},
	year = {2015},
	publisher = {The Royal Society},
	abstract = {There are many cases where one needs to limit the X-ray dose, or the number of projections, or both, for high frame rate (fast) imaging. Normally, it improves temporal resolution but reduces the spatial resolution of the reconstructed data. Fortunately, the redundancy of information in the temporal domain can be employed to improve spatial resolution. In this paper, we propose a novel regularizer for iterative reconstruction of time-lapse computed tomography. The non-local penalty term is driven by the available prior information and employs all available temporal data to improve the spatial resolution of each individual time frame. A high-resolution prior image from the same or a different imaging modality is used to enhance edges which remain stationary throughout the acquisition time while dynamic features tend to be regularized spatially. Effective computational performance together with robust improvement in spatial and temporal resolution makes the proposed method a competitive tool to state-of-the-art techniques.},
	isbn = {1471-2962},
	issn = {1364-503X},
	doi = {10.1098/rsta.2014.0389},
	author = {Kazantsev, Daniil and Van Eyndhoven, Geert and Lionheart, William R. B. and Withers, Philip J. and Katherine J Dobson and McDonald, S. A. and Atwood, R and Lee, Peter D.}
}
@article {1606,
	title = {An iterative CT reconstruction algorithm for fast fluid flow imaging},
	journal = {IEEE Transactions on Image Processing},
	volume = {24},
	year = {2015},
	pages = {4446-4458},
	abstract = {The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique.

In this paper, a new iterative CT reconstruction algorithm for improved temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. Firstly, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Secondly, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary.

Quantitative and qualitative results on different simulation experiments and a real neutron tomography dataset show that, in comparison state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, temporal resolution can be substantially increased and thus fluid flow experiments with faster dynamics can be performed.},
	issn = {1057-7149},
	doi = {10.1109/TIP.2015.2466113},
	author = {Van Eyndhoven, Geert and Kees Joost Batenburg and Kazantsev, Daniil and Vincent Van Nieuwenhove and Lee, Peter D. and Katherine J Dobson and Jan Sijbers}
}
