Dual-energy CT imaging with limited-angular-range data
Buxin Chen, Zheng Zhang, Dan Xia, Emil Y. Sidky, and Xiaochuan Pan

TL;DR
This paper introduces a novel directional-total-variation (DTV) algorithm for dual-energy CT imaging with limited-angular-range data, significantly reducing artifacts and enabling accurate physical quantity estimation from less than 180° scans.
Contribution
The study develops a convex optimization-based DTV algorithm tailored for LAR DECT, demonstrating improved image quality and quantitative accuracy over existing methods.
Findings
Substantially reduced artifacts in LAR images.
Accurate estimation of atomic number and iodine concentration.
Comparable results to full-angular-range DECT.
Abstract
In dual-energy computed tomography (DECT), low- and high- kVp data are collected often over a full-angular range (FAR) of . While there exists strong interest in DECT with low- and high-kVp data acquired over limited-angular ranges (LARs), there remains little investigation of image reconstruction in DECT with LAR data. Objective: We investigate image reconstruction with minimized LAR artifacts from low- and high-kVp data over LARs of by using a directional-total-variation (DTV) algorithm. Methods: Image reconstruction from LAR data is formulated as a convex optimization problem in which data- is minimized with constraints on image's DTVs along orthogonal axes. We then achieve image reconstruction by applying the DTV algorithm to solve the optimization problem. We conduct numerical studies from data generated over arcs of LARs, ranging from …
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