| Abstract: |
Limited-angle (LA) dual-energy (DE) cone-beam CT (CBCT) is considered an ideal 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 insufficient projections. In this work, we aim to perform optimization-based image reconstruction for LA-DECBCT with high computation efficiency. A structural similarity-based regularization term is introduced into the joint image reconstruction of DECBCT for suppression of LA-artifacts based on the facts that i) the DECBCT images share the same anatomical structures, and ii) the complete anatomical information is acquired in the LA-DECBCT projection data. The proposed iterative reconstruction method is evaluated using a Catphan phantom study and a digital phantom study, showing its feasibility for efficient image reconstruction in LA-DECBCT. © 2025 SPIE. |
