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Fast and Accurate 3D X ray Image Reconstruction for Non Destructive Test Industrial Applications

Abstract : 2D and 3D X-ray Computed Tomography (CT) is widely used in medical imaging as well as in Non Destructive Testing (NDT) for industrial applications. In both domains, there is a need to reduce the number of projections. In some cases we may also be limited in angles. The measured data are always with errors (measurement and modelling errors). We are consequently almost always in the situation of ill-posed inverse problems. The role of the probabilistic methods and the prior modelling become crucial. For prior modelling, in particular in NDT applications, the object under examination is composed with several homogeneous materials, with several continuous blocs separated by some discontinuities and contours. This type of object is called the piecewise-continuous object. The focus of this thesis on the reconstruction of the picewise continuous or constant, or more generally piecewise homogeneous objects. In summary two main methods are proposed in the context of the Bayesian inference. The first method consists in reconstructing the object while enforcing the sparsity of the discrete Haar transformation coefficients of the object. A hierarchical Bayesian model is proposed. In this method, the unknown variables and parameters are estimated and the hyper-parameters are initialized according to the definition of prior models. The second method reconstruct objects while the contours are estimated simultaneously. The piecewise continuous object is modeled by a non-homogeneous Markovian model, which depends on the gradient of the object, while the gradient also depends on the estimation of the object. In this methods, the semi-supervised system model is also achieved, with the parameters estimated automatically. Both methods are adapted to the 3D big data size reconstructions, in which the GPU processor is used to accelerate the computation. The methods are validated with both simulated and real data, and are compared with several conventional state-of-the-art methods.
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Submitted on : Monday, January 29, 2018 - 6:36:08 PM
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  • HAL Id : tel-01695872, version 1


Li Wang. Fast and Accurate 3D X ray Image Reconstruction for Non Destructive Test Industrial Applications. Image Processing [eess.IV]. Université Paris-Saclay, 2017. English. ⟨NNT : 2017SACLS362⟩. ⟨tel-01695872⟩



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