X-ray and ultrasonic tomography

Munshi, P.

doi:10.1784/insi.45.1.47.52601

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…Computed tomography (CT) is an imaging technique that is used to create a three-dimensional image of an object from a series of twodimensional data [1][2][3] . CT provides the details of interior structures, such as geometry, composition and physical density of the object, and has varied engineering applications [4] .…”

Section: Introductionmentioning

confidence: 99%

Simulation of beam hardening in X-ray tomography and its correction using linearisation and pre-filtering approaches

Arunmuthu¹,

Ashish²,

Saravanan³

et al. 2013

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CTBeam hardening is one of the major artefacts, which arises due to the polychromatic nature of the X-ray source, that reduces the quality of the reconstructed image in X-ray computed tomography. This paper describes the simulation of a tomogram with beam hardening and its correction using linearisation and pre-filtering methods. The simulation studies show that 70% of the maximum energy is required for full object penetration and to obtain minimum beam hardening. Also, the pre-filtering offers better beam hardening correction due to the removal of low-energy photons. The simulation results are found to be in good agreement with the experimental results. After beam hardening correction, 3D visualisation and dimensional analysis of a stator motor core specimen has been demonstrated.

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Section: Introductionmentioning

confidence: 99%

Simulation of beam hardening in X-ray tomography and its correction using linearisation and pre-filtering approaches

Arunmuthu¹,

Ashish²,

Saravanan³

et al. 2013

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A Phenomic Approach to Genetic Algorithms for Reconstruction of Gene Networks

D’Souza¹,

Sekaran

Kandasamy

2010

Communications in Computer and Information Science

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Performance evaluation of iterative tomography algorithms for incomplete projection data

Mishra¹,

Longtin²,

Singh³

et al. 2004

Appl. Opt.

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Projection data obtained through optical techniques for tomographic measurements, such as interferometry for refractive-index-based measurements, are often incomplete. This is due to limitations in the optical system, data storage, and alignment and vignette issues. Algebraic iterative reconstruction techniques are usually favored for such incomplete projections. A number of iterative algorithms, based on additive and multiplicative corrections, are used with a known simulated phantom and noise source to assess the reconstruction performance of incomplete data sets. In addition, we present reconstructions using experimental data obtained from a coherent gradient sensing interferometer for a steady temperature field in a fluid medium. We tested the algorithms using the simulated data set for incompleteness conditions similar to those found in the experimental data, and the best-performing algorithm is identified.

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X-ray and ultrasonic tomography

Cited by 3 publications

References 16 publications

Simulation of beam hardening in X-ray tomography and its correction using linearisation and pre-filtering approaches

Simulation of beam hardening in X-ray tomography and its correction using linearisation and pre-filtering approaches

A Phenomic Approach to Genetic Algorithms for Reconstruction of Gene Networks

Performance evaluation of iterative tomography algorithms for incomplete projection data

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