X-ray Computed Tomography using a Sparsity Enforcing Prior Model Based on Haar Transformation in a Bayesian Framework

• Autorzy: Wang L. , Mohammad-Djafari A. , Gac N.

Identyfikatory

DOI

10.3233/FI-2017-1594

• Języki publikacji: EN

Abstrakty

EN

X-ray Computed Tomography (CT) has become a hot topic in both medical and industrial applications in recent decades. Reconstruction by using a limited number of projections is a significant research domain. In this paper, we propose to solve the X-ray CT reconstruction problem by using the Bayesian approach with a hierarchical structured prior model basing on the multilevel Haar transformation. In the proposed model, the multilevel Haar transformation is used as the sparse representation of a piecewise continuous image, and a generalized Student-t distribution is used to enforce its sparsity. The simulation results compare the performance of the proposed method with some state-of-the-art methods.

Słowa kluczowe

EN

computed tomography; CT; Bayesian approach; hierarchical model; generalized student-t distribution; joint maximum a posterior; JMAP

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2017
• Tom: Vol. 155, nr 4
• Strony: 449--480
• Opis fizyczny: Bibliogr. 68 poz., rys., tab., wykr.

Twórcy

autor

Wang L.

• Laboratoire des Signaux et Système, CentraleSupélec, CNRS, Université Paris Sud, Université Paris-Saclay, 3, Rue Joliot-Curie, 91192 Gif-sur-Yvette, France

autor

Mohammad-Djafari A.

• Laboratoire des Signaux et Système, CentraleSupélec, CNRS, Université Paris Sud, Université Paris-Saclay, 3, Rue Joliot-Curie, 91192 Gif-sur-Yvette, France

autor

Gac N.

• Laboratoire des Signaux et Système, CentraleSupélec, CNRS, Université Paris Sud, Université Paris-Saclay, 3, Rue Joliot-Curie, 91192 Gif-sur-Yvette, France

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).