To address artifacts and shape deviations in cone-beam CT (CBCT) caused by geometric misalignments, this study proposes a phantom-free two-stage calibration scheme. Detector pre-correction is first performed to lay a foundation for subsequent rotation-axis optimization, with the latter leveraging a Sharpness-Maximized Matching (SMM) strategy as the core. Specifically, detector pre-correction is achieved via symmetry-aware SIFT matching, adaptive sampling, and doubly-weighted optimization to estimate the detector’s horizontal offset. For rotation-axis optimization, an improved evaluation function is introduced under the SMM framework, and the optimal horizontal offset of the rotation axis is determined through iterative reconstruction within a predefined search range. Experiments on a set of industrial workpiece projection data demonstrate that the proposed two-stage scheme effectively eliminates artifacts, outperforms SAM and WAC in both image sharpness and measurement accuracy, and enables high-precision non-destructive testing without relying on dedicated phantoms.

Yulong Zhang, Zhen Zhang, Jianqiang Mei. Dual-Stage Geometric Calibration for Artifact Suppression in Cone-Beam CT. Academic Journal of Computing & Information Science (2026), Vol. 9, Issue 1: 56-62. https://doi.org/10.25236/AJCIS.2026.090107.

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