A Feasibility Study of Low-Dose Single-Scan Dual-Energy Cone-Beam CT in Many-View Under-Sampling Framework

• Published in: IEEE transactions on medical imaging Vol. 36; no. 12; pp. 2578 - 2587
• Main Authors: Lee, Donghyeon, Lee, Jiseoc, Kim, Hyoyi, Lee, Taewon, Soh, Jeongtae, Park, Miran, Kim, Changhwan, Lee, Yeon Ju, Cho, Seungryong
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.12.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Algorithms; Beams (radiation); Computed tomography; Cone-beam computed tomography; Cone-Beam Computed Tomography - methods; Data processing; Detectors; dual-energy CT; Electron tubes; Energy; Feasibility Studies; Filtering algorithms; Head - diagnostic imaging; Humans; Image processing; Image Processing, Computer-Assisted - methods; Image reconstruction; low-dose CT; Noise levels; Phantoms, Imaging; Projection; Slits; X ray sources; X-ray imaging
• ISSN: 0278-0062; 1558-254X; 1558-254X
• DOI: 10.1109/TMI.2017.2765760

A single-scan dual-energy low-dose cone-beam CT (CBCT) imaging technique that exploits a multi-slit filter is proposed in this paper. The multi-slit filter installed between the x-ray source and the scanned object is reciprocated during a scan. The x-ray beams through the slits would generate relatively low-energy x-ray projection data, while the filtered beams would make high-energy projection data. An iterative image reconstruction algorithm that uses an adaptive-steepest-descent method to minimize image total-variation under the constraint of data fidelity was applied to reconstructing the image from the low-energy projection data. Since the high-energy projection data suffer from a substantially high noise level due to the beam filtration, we have developed a new algorithm that exploits the joint sparsity between the low- and high-energy CT images for image reconstruction of the high-energy CT image. The proposed image reconstruction algorithm uses a gradient magnitude image (GMI) of the low-energy CT image by regularizing the difference of GMIs of the low- and high-energy CT images to be minimized. The feasibility of the proposed technique has been demonstrated by the use of various phantoms in the experimental CBCT setup. Furthermore, based on the proposed dual-energy imaging, a material differentiation was performed and its potential utility has been shown. The proposed imaging technique produced promising results for its potential application to a low-dose single-scan dual-energy CBCT.