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Updated: Sep 18, 2025

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
Published on: February 23, 2024
Optimization-based image reconstruction regularized with inter-spectral structural similarity for limited-angle
Junbo Peng1, Tonghe Wang2, Huiqiao Xie2
1Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322, United States of America.
Abstract:
Objective. Limited-angle dual-energy (DE) cone-beam CT (CBCT) is considered as a potential solution to achieve fast and low-dose DE imaging on current CBCT scanners without hardware modification. However, its clinical implementations are hindered by the challenging image reconstruction from limited-angle projections. While optimization-based and deep learning-based methods have been proposed for image reconstruction, their utilization is limited by the requirement for x-ray spectra measurement or paired datasets for model training. This work aims to facilitate the clinical applications of fast and low-dose DE-CBCT by developing a practical solution for image reconstruction in limited-angle DE-CBCT.Approach. An inter-spectral structural similarity-based regularization was integrated into the iterative image reconstruction in limited-angle DE-CBCT. By enforcing the similarity between the DE images, limited-angle artifacts were efficiently reduced in the reconstructed DECBCT images. The proposed method was evaluated using two physical phantoms and three digital phantoms, demonstrating its efficacy in quantitative DECBCT imaging.Main results. In all the studies, the proposed method achieves accurate image reconstruction without visible residual artifacts from limited-angle DE-CBCT projection data. In the digital phantom studies, the proposed method reduces the mean-absolute-error from 309/290 HU to 14/20 HU, increases the peak signal-to-noise ratio from 40/39 dB to 70/67 dB, and improves the structural similarity index measurement from 0.74/0.72-1.00/1.00.Significance. The proposed method can efficiently reduce limited-angle artifacts during the image reconstruction, enabling quantitative DE-CBCT with comparable data acquisition time and radiation dose to that of a single-energy scan on current onboard scanners without hardware modification. This work is of great clinical significance and can boost the clinical application of DE-CBCT in image-guided radiation therapy and surgical interventions.
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