A generalized simultaneous algebraic reconstruction technique (GSART) for dual-energy X-ray computed tomography

Author:

Lee Donghyeon1,Yun Sungho1,Soh Jeongtae1,Lim Sunho1,Kim Hyoyi1,Cho Seungryong12

Affiliation:

1. Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea

2. KAIST Institutes for ITC, AI, and HST, Korea Advanced Institute of Science and Technology, Daejeon, Korea

Abstract

BACKGROUND: Dual-energy computed tomography (DECT) is a widely used and actively researched imaging modality that can estimate the physical properties of an object more accurately than single-energy CT (SECT). Recently, iterative reconstruction methods called one-step methods have received attention among various approaches since they can resolve the intermingled limitations of the conventional methods. However, the one-step methods typically have expensive computational costs, and their material decomposition performance is largely affected by the accuracy in the spectral coefficients estimation. OBJECTIVE: In this study, we aim to develop an efficient one-step algorithm that can effectively decompose into the basis material maps and is less sensitive to the accuracy of the spectral coefficients. METHODS: By use of a new loss function that employs the non-linear forward model and the weighted squared errors, we propose a one-step reconstruction algorithm named generalized simultaneous algebraic reconstruction technique (GSART). The proposed algorithm was compared with the image-domain material decomposition and other existing one-step reconstruction algorithm. RESULTS: In both simulation and experimental studies, we demonstrated that the proposed algorithm effectively reduced the beam-hardening artifacts thereby increasing the accuracy in the material decomposition. CONCLUSIONS: The proposed one-step reconstruction for material decomposition in dual-energy CT outperformed the image-domain approach and the existing one-step algorithm. We believe that the proposed method is a practically very useful addition to the material-selective image reconstruction field.

Publisher

IOS Press

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiology, Nuclear Medicine and imaging,Instrumentation,Radiation

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