Open AccessMoVIT: a tomographic reconstruction framework for 4D-CT
Author(s) -
Vincent Van Nieuwenhove,
Jan De Beenhouwer,
Jelle Vlassenbroeck,
Mark W. Brennan,
Jan Sijbers
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.019236
Subject(s) - iterative reconstruction , rotation (mathematics) , computer science , image quality , image resolution , tomographic reconstruction , computer vision , frame (networking) , temporal resolution , tomography , sample (material) , artificial intelligence , algorithm , optics , image (mathematics) , physics , telecommunications , thermodynamics
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.