Abstract
Traditional computed tomography (CT) systems are cumbersome to transport and thus difficult to apply in field environments or space-constrained scenarios, which necessitates the development of rapid reconstruction techniques for portable cone-beam CT (CBCT) systems. However, the portability and temporary assembly nature of such systems pose significant challenges to high-precision spatial positioning, which has become a core bottleneck limiting reconstruction quality. Conventional calibration methods rely on complex, high-cost stereoscopic phantoms, with inherent drawbacks including prolonged calibration time (1-2 h) and poor portability. These methods fail to meet the on-site rapid deployment requirements of portable systems and cannot satisfy the multidimensional geometric parameter calibration needs. To overcome this limitation, this study draws on machine vision calibration principles to propose, for the first time, an equivalent geometric model adapted to the seven-parameter assembled portable CT system. Furthermore, an industrial CT geometric parameter calibration method based on a circular array planar calibration board is developed, and the accuracy of the proposed model and algorithm is verified through reconstruction experiments. Experimental results show that the proposed method yields subpixel reprojection error and higher reconstruction resolution than conventional three-parameter industrial CT, with total calibration data acquisition within 5 min, remarkably outperforming traditional stereoscopic phantom-based methods. Its accuracy and efficiency satisfy the on-site calibration requirements of portable industrial CT. Featuring low cost and fast deployment, it enables traditional portable DR equipment to be upgraded to CT capability, which alleviates the high-cost bottleneck of portable CT and provides key technical support for its market promotion and application extension.
| Original language | English |
|---|---|
| Article number | 4504213 |
| Journal | IEEE Transactions on Instrumentation and Measurement |
| Volume | 75 |
| DOIs | |
| State | Published - 2026 |
Keywords
- Computer vision
- cone-beam computed tomography (CBCT) reconstruction
- geometric calibration
- image processing
- portable industrial computed tomography (CT)
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