X-Ray scattering tomography

Gorshkov, V. A.; Kroening, M.; Anosov, Y.V.; Dorjgochoo, O.

doi:10.1080/10589750500191026

Cited by 11 publications

(9 citation statements)

References 2 publications

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“…Although the technology of such detectors has not yet reached the same level of maturity as the one used in conventional imaging (CT, SPECT, PET), scientists have proposed and studied in the last decades different bi-dimensional systems, called Compton scattering tomography (CST), see e.g. [23,27,7,1,3,5,6,8,12,13,16,19,25,4,17,30]. It is also possible to consider interior sources, for instance via the insertion of radiotracers like in SPECT.…”

Section: Lnmentioning

confidence: 99%

3D Compton scattering imaging: study of the spectrum and contour reconstruction

Rigaud

2019

Preprint

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3D Compton scattering imaging is an upcoming concept focusing on exploiting the photons scattered, following on from the so-called Compton effect, by the atomic structure of an object under study. This phenomenon rules the collision of particles with electrons and describes their energy loss after scattering. Consequently, a monochromatic source leads to a polychromatic response on the camera. Assuming the camera to collect continuously the photons in terms of energy, we model the measured spectrum for first-and second-order scattering. The second-order scattered radiation reveals itself to be structurally smoother than the radiation of first-order. Therefore, the contours of the electron density are essentially encoded within the first-order scattering radiation and can be recovered from the full spectrum using a filtered backprojection kind inversion technique. Our main results, modeling and reconstruction scheme, are successfully implemented on synthetic and Monte-Carlo data.

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Section: Lnmentioning

confidence: 99%

3D Compton scattering imaging: study of the spectrum and contour reconstruction

Rigaud

2019

Preprint

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“…where mc 2 = 511 keV represents the energy of an electron at rest. Measuring accurately the variations of the energy can thus be interpreted as scattering events characterized geometrically by the scattering angle which is the foundation of Compton scattering tomography (CST), see [3,5,8,10,12,16,17,20,11,29,6,21,22,32,31,33,37,43].…”

Section: Introductionmentioning

confidence: 99%

Imaging based on Compton scattering: model-uncertainty and data-driven reconstruction methods

Gödeke¹,

Rigaud²

2022

Preprint

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The recent development of scintillation crystals combined with γrays sources opens the way to an imaging concept based on Compton scattering, namely Compton scattering tomography (CST). The associated inverse problem rises many challenges: non-linearity, multiple order-scattering and high level of noise. Already studied in the literature, these challenges lead unavoidably to uncertainty of the forward model. This work proposes to study exact and approximated forward models and develops two data-driven reconstruction algorithms able to tackle the inexactness of the forward model. The first one is based on the projective method called regularized sequential subspace optimization (RESESOP). We consider here a finite dimensional restriction of the semi-discrete forward model and show its well-posedness and regularisation properties. The second one considers the unsupervised learning method, deep image prior (DIP), inspired by the construction of the model uncertainty in RESESOP. The methods are validated on Monte-Carlo data.

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“…Although the technology involved in imaging the scattered radiation has not yet reached the same level of maturity as the one used in conventional imaging (CT, SPECT, PET), scientists have proposed and studied in the last decades different bi-dimensional systems, called Compton scattering tomography (CST), see, e.g. [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32]. More recently, an important application was proposed in radiation oncology for treatment planning (the electron density is known as reliable information) and image guidance/patient setup for treatments, see [33,34].…”

Section: Introductionmentioning

confidence: 99%

Reconstruction algorithm for 3D Compton scattering imaging with incomplete data

Rigaud

Hahn

2020

Inverse Problems in Science and Engineering

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Compton scattering describes the scattering of a photon after its collision with an electron. The recent developments of spectral cameras, able to collect photons in terms of energy, open the way to a new imaging concept: 3D Compton scattering imaging (CSI), which seeks to exploit the scattered radiation as a vector of information while a specimen of interest is illuminated by a monochromatic ionizing source. Focusing on modelling the first-order scattering, image reconstruction from CSI data remains a difficult challenge. In particular, physical constraints (detector and architecture of the scanner) lead to various incompleteness scenario within the data and thus streak artifacts when using filtered backprojection type formulas. This paper addresses the problem of recovering an object under study using CSI data subject to incompleteness and assuming only first-order scattering. The proposed method consists of suitably tuning the multiplicative Kaczmarz algorithm and is implemented and tested for two architectures of the scanner. Furthermore, the modality on CSI considered here presents the advantage of not requiring any rotation of the source or object.

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X-Ray scattering tomography

Cited by 11 publications

References 2 publications

3D Compton scattering imaging: study of the spectrum and contour reconstruction

3D Compton scattering imaging: study of the spectrum and contour reconstruction

Imaging based on Compton scattering: model-uncertainty and data-driven reconstruction methods

Reconstruction algorithm for 3D Compton scattering imaging with incomplete data

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