MoVIT: a tomographic reconstruction framework for 4D-CT

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.

Improving image quality in fast, time-resolved micro-CT by weighted back projection

“…In contrast, weighted back projection is less suited for dynamic processes which consist mainly of deformation, such as the deformation of foams 8 , since in those cases no static regions can be identified and prior knowledge on locations in the foam can not be used as a 1-to-1 mapping with future locations. As a future prospect, weighted back projection could be combined with motion registration [29][30][31] , deforming not only the volume itself but the weight volume with it, to include more possible applications.…”

Motion compensated micro-CT reconstruction for in-situ analysis of dynamic processes

“… 25 , 26 ). It is assumed that the deformation fields can be described by dense displacement fields , known in advance 29 or estimated through any registration technique. Important here is the indexation ‘ p ’, which indicates that the describes the displacement of the object at time instant t p , when the projection P p is acquired.…”

“…there is no clear distinction between reference and deformed states, DVC and CT reconstruction can be integrated to enhance the quality of both, in terms of signal-to-noise ratio (SNR), temporal and spatial resolution. The idea to exploit this synergy between DVC and motion compensated CT reconstruction has been explored for medical CT several years ago 25 – 28 , and has recently also found its way into high-resolution X-ray CT 29 , 30 .…”

Ab initio nonrigid X-ray nanotomography

“…We demonstrate here an application of nonrigid geometry computed tomography (NCT) with a self-consistent method for motion estimation directly from the measured data set. Our approach builds on previous work on 4D-CT imaging but reformulates the optimization task in order to avoid the significant increase of the degrees of freedom that would be needed to recover a general 4D-CT time-evolving reconstruction 1,10–12 . In addition, our method accounts for a continuous deformation of the sample structure during data acquisition, i.e., nonrigid sample changes, as well as rigid sample motion that is commonly present due to insufficient stability of nanotomography setups.…”