Data fusion in neutron and X-ray computed tomography

Schrapp, Michael; Goldammer, Matthias; Schulz, Michael; Issani, Siraj; Bhamidipati, Suryanarayana; Böni, P.

doi:10.1063/1.4900515

Cited by 7 publications

(4 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When imaging an object with multiple modalities, common structural information should be detectable. In the RSART method, published in [1], a fused image was generated by averaging the neutron and X-Ray image with neutron image matching the mean and standard deviation of the X-Ray image, except where the quality metric for a modality drops below a threshold at which point the average value is replaced with the value from the least starved modality. This fused image is then used as a constant prior image in a regularized SART reconstruction.…”

Section: Fused Image Regularizationmentioning

confidence: 99%

“…The goal of employing these techniques is to improve the reconstruction of object geometry and structures while reducing missing data artefacts. The fused image component of this multi-regularized reconstruction builds on the method published in [1], which used a pre-processed fused image as a prior for reconstruction. Here, instead of a fixed pre-processed prior, an iteratively updated fused image was used as a regularization term.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint Bi-Modal Tomographic Reconstruction from Observations with Missing Data

Leatherland,

Bazin,

Aldrich-Smith

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

A method for tomographic reconstruction of bi-modal data sets using cross modal regularization was developed. The method constrains the Simultaneous Algebraic Reconstruction Technique by using clustering-based segmented images and quality controlled fused images, to jointly regularize the reconstruction of structures imaged with different methods. The joint regularized reconstruction method was tested using a synthetic X-Ray and neutron data set with a mix of attenuation driven data starvation. Assuming consistent material boundaries in the different imaging modalities, it was shown that improvements in terms of the Feature Similarity Index Measure are made compared to a traditional SART-TV reconstruction. UK Ministry of Defence ©Crown Owned Copyright 2023/AWE

show abstract

Section: Fused Image Regularizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Joint Bi-Modal Tomographic Reconstruction from Observations with Missing Data

Leatherland,

Bazin,

Aldrich-Smith

et al. 2023

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

show abstract

“…The α parameter can be varied to highlight features either from the neutron image or from the γ-ray alternative. A similar technique can be applied using the data fusion methodology reported in [20].…”

Section: Qualitative Observationsmentioning

confidence: 99%

Concealed nuclear material identification via combined fast-neutron/γ-ray computed tomography (FNGCT): a Monte Carlo study

Licata

Joyce

2018

J. Inst.

View full text Add to dashboard Cite

The potential of a combined and simultaneous fast-neutron/γ-ray computed tomography technique using Monte Carlo simulations is described. This technique is applied on the basis of a hypothetical tomography system comprising an isotopic radiation source (americium-beryllium) and a number (13) of organic scintillation detectors for the production and detection of both fast neutrons and γ rays, respectively. Via a combination of γ-ray and fast neutron tomography the potential is demonstrated to discern nuclear materials, such as compounds comprising plutonium and uranium, from substances that are used widely for neutron moderation and shielding. This discrimination is achieved on the basis of the difference in the attenuation characteristics of these substances. Discrimination of a variety of nuclear material compounds from shielding/moderating substances (the latter comprising lead or polyethylene for example) is shown to be challenging when using either γ-ray or neutron tomography in isolation of one another. Much-improved contrast is obtained for a combination of these tomographic modalities. This method has potential applications for in-situ, non-destructive assessments in nuclear security, safeguards, waste management and related requirements in the nuclear industry. K : Computerized Tomography (CT) and Computed Radiography (CR); Inspection with gamma rays; Inspection with neutrons; Neutron detectors (cold, thermal, fast neutrons) 1Corresponding author.

show abstract

“…This can be very difficult and often requires a lot of computational power. Then there are methods that use additional information: There are several multimodal fusion approaches like the combination of X-ray CT with tactile and optical sensors [23] or X-ray CT with neutron CT [24]. These methods obviously need more than one sensor system and, therefore, can be very expensive and complicated.…”

Section: Introductionmentioning

confidence: 99%

Artifact reduction in X-ray computed tomography by multipositional data fusion using local image quality measures

Herl¹,

Hiller²,

Sauer³

2019

eJNDT

View full text Add to dashboard Cite

Metal artifacts are still a major problem in X-ray industrial computed tomography. In order to reduce metal artifacts and increase the image quality of X-ray CT-scans, we suggest using projection data from multiple scans with differently positioned object orientations. We present two different approaches for multipositional CT, which are especially effective for multimaterial objects with high absorbing metal parts. On one hand, we reconstruct the different scans separatly, estimate the local quality of the resulting volumes and then fuse these volumes to an optimized volume. On the other hand, we introduce smART (shrinking merged Algebraic Reconstruction Technique) and merge sinograms of different scans, estimate the reliability of each projection pixel and then reconstruct the merged sinogram with an adapted SART reconstruction method. We demonstrate our approaches on simulations and on measurement data and are able to show a significant reduction of image artifacts qualitatively and quantitatively with the help of dimensional measurement results.

show abstract

Data fusion in neutron and X-ray computed tomography

Cited by 7 publications

References 21 publications

Joint Bi-Modal Tomographic Reconstruction from Observations with Missing Data

Joint Bi-Modal Tomographic Reconstruction from Observations with Missing Data

Concealed nuclear material identification via combined fast-neutron/γ-ray computed tomography (FNGCT): a Monte Carlo study

Artifact reduction in X-ray computed tomography by multipositional data fusion using local image quality measures

Contact Info

Product

Resources

About