3D Algebraic Iterative Reconstruction for Cone-Beam X-Ray Differential Phase-Contrast Computed Tomography

Fu, Jian; Hu, Xinhua; Velroyen, Astrid; Bech, Martin; Ji, Ming; Pfeiffer, Franz

doi:10.1371/journal.pone.0117502

Cited by 17 publications

(10 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such an advanced scheme could also be combined with iterative reconstruction (IR) methods including algebraic iterative reconstruction and statistical iterative reconstruction [ 37 – 40 ]. In particular with statistical iterative reconstruction (SIR) schemes, where the pixels could be assigned a weight corresponding to their noise levels [ 41 ].…”

Section: Discussionmentioning

confidence: 99%

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography

et al. 2017

Self Cite

View full text Add to dashboard Cite

Phase-contrast x-ray computed tomography (PCCT) is currently investigated as an interesting extension of conventional CT, providing high soft-tissue contrast even if examining weakly absorbing specimen. Until now, the potential for dose reduction was thought to be limited compared to attenuation CT, since meaningful phase retrieval fails for scans with very low photon counts when using the conventional phase retrieval method via phase stepping. In this work, we examine the statistical behaviour of the reverse projection method, an alternative phase retrieval approach and compare the results to the conventional phase retrieval technique. We investigate the noise levels in the projections as well as the image quality and quantitative accuracy of the reconstructed tomographic volumes. The results of our study show that this method performs better in a low-dose scenario than the conventional phase retrieval approach, resulting in lower noise levels, enhanced image quality and more accurate quantitative values. Overall, we demonstrate that the lower statistical limit of the phase stepping procedure as proposed by recent literature does not apply to this alternative phase retrieval technique. However, further development is necessary to overcome experimental challenges posed by this method which would enable mainstream or even clinical application of PCCT.

show abstract

Section: Discussionmentioning

confidence: 99%

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Talbot-Lau grating interferometer (TLGI) XCT introduces two additional imaging modalities: differential phase contrast (DPC) due to refraction and dark-field contrast (DFC) due to scattering. This method is continuously evolving by improved grating design [4], advanced reconstruction techniques [5] and image processing routines [6], while suitable materials science applications have been identified [7][8][9][10]. Up to now, DFC turns out to be the key imaging modality for materials science, since it is capable of revealing interface contrast of internal structures and defects such as small pores, gaps or cracks in the sub-voxel region that can be even smaller than the spatial resolution of the XCT system [11,12].…”

Section: Introductionmentioning

confidence: 99%

Porosity Determination of Carbon and Glass Fibre Reinforced Polymers Using Phase-Contrast Imaging

et al. 2018

View full text Add to dashboard Cite

This paper presents multi-modal image data of different fibre reinforced polymer samples acquired with a desktop Talbot-Lau grating interferometer (TLGI) X-ray computed tomography (XCT) system and compare the results with images acquired using conventional absorption-based XCT. Two different fibre reinforced polymer samples are investigated: (i) a carbon fibre reinforced polymer (CFRP) featuring a copper mesh embedded near the surface for lightning conduction and (ii) a short glass fibre reinforced polymer (GFRP) sample. The primary goal is the non-destructive detection of internal defects such as pores and the quantification of porosity. TLGI provides three imaging modalities including attenuation contrast (AC) due to absorption, differential phase contrast (DPC) due to refraction and dark-field contrast (DFC) due to scattering. In the case of the CFRP sample, DPC is less prone to metal streak artefacts improving the detection of pores that are located close to metal components. In addition, results of a metal artefact reduction (MAR) method, based on sinogram inpainting and an image fusion concept for AC, DPC and DPC, are presented. In the case of the GFRP sample, DPC between glass fibres and matrix is lower compared to AC while DPC shows an increased contrast between pores and its matrix. Porosity for the CFRP sample is determined by applying an appropriate global thresholding technique while an additional background removal is necessary for the GFRP sample. Keywords X-ray computed tomography • Talbot-Lau grating interferometer • Differential phase contrast • Carbon and glass fibre reinforced polymers • Porosity B Christian Gusenbauer

show abstract

“…Broadly, regularization works by including prior knowledge about the object into the reconstruction process, promoting, e.g., the piecewise smoothness of the reconstruction. There have been several recent efforts to use these techniques for DPC CT reconstruction: [19] explores 3D unregularized iterative reconstruction; [20] uses algebraic iterative reconstruction with no regularization for 3D reconstruction; [21] and [22] use regularized iterative reconstruction in 2D; and [23] and our own [24] perform 3D regularized iterative reconstruction slice-by-slice, where the reconstruction (including the regularization) occurs on a series of 2D slices, which are then concatenated to form a 3D reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Fast 3D reconstruction method for differential phase contrast X-ray CT

McCann¹,

Nilchian²,

Stampanoni³

et al. 2016

Opt. Express

View full text Add to dashboard Cite

We present a fast algorithm for fully 3D regularized X-ray tomography reconstruction for both traditional and differential phase contrast measurements. In many applications, it is critical to reduce the X-ray dose while producing high-quality reconstructions. Regularization is an excellent way to do this, but in the differential phase contrast case it is usually applied in a slice-by-slice manner. We propose using fully 3D regularization to improve the dose/quality trade-off beyond what is possible using slice-by-slice regularization. To make this computationally feasible, we show that the two computational bottlenecks of our iterative optimization process can be expressed as discrete convolutions; the resulting algorithms for computation of the X-ray adjoint and normal operator are fast and simple alternatives to regridding. We validate this algorithm on an analytical phantom as well as conventional CT and differential phase contrast measurements from two real objects. Compared to the slice-by-slice approach, our algorithm provides a more accurate reconstruction of the analytical phantom and better qualitative appearance on one of the two real datasets. (14), 2961-2964 (1996). 10. S. W. Wilkins, T. E. Gureyev, D. Gao, A. Pogany, and A. W. Stevenson, "Phase-contrast imaging using polychromatic hard X-rays," Nature 384(6607), 335-338 (1996). #261788Received 6 11. U. Bonse and M. Hart, "An X-ray interferometer," Appl. Phys. Lett. 6(8), 155-156 (1965). 12. A. Momose, T. Takeda, Y. Itai, and K. Hirano, "Phase-contrast X-ray computed tomography for observing biological soft tissues," Nat. Med. 2(4), 473-475 (1996

show abstract

3D Algebraic Iterative Reconstruction for Cone-Beam X-Ray Differential Phase-Contrast Computed Tomography

Cited by 17 publications

References 50 publications

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography

Porosity Determination of Carbon and Glass Fibre Reinforced Polymers Using Phase-Contrast Imaging

Fast 3D reconstruction method for differential phase contrast X-ray CT

Contact Info

Product

Resources

About