Poster Poster Program Diagnostic and Interventional Radiology Physics

Development and Characterization of a High-Resolution Photon-Counting Tabletop Cone-Beam CT System and End-to-End Module for Streamlined Workflow

Abstract
Purpose

Photon-counting detector (PCD)–based cone-beam CT (CBCT) is gaining increasing interest for its potential to enable high-resolution and spectrally rich imaging. This study develops a tabletop PCD-CBCT system as a research platform and reports our progress in its design, construction, and integrated imaging workflow

Methods

A tabletop PCD–based CBCT system was developed by integrating a microfocus X-ray source (HamamatsuL10951, 110kV/445µA, 15-80 µm nominal spot size), a precision rotation stage (Velmex B4872TS), and a high-resolution PCD (Varex, THOR, 5 × 20 cm² active area, 100 µm pixel size) within a compact mechanical framework. A custom 3D Slicer module was implemented to provide an end-to-end imaging workflow, including hardware control, data acquisition, detector calibration for pixel response nonuniformity correction, geometric calibration, image reconstruction, and visualization. System performance was evaluated using a Shelley quality assurance phantom acquired at 110 kV and 154 µA with 1200 projections over a full 360° rotation, using low- (26 keV) and high-energy (56 keV) threshold channels.

Results

Geometric calibration determined a source-to-detector distance of 439.1 mm and a source-to-axis distance of 221.7 mm. The integrated workflow enabled fully automated execution of the imaging pipeline. Reconstructed Shelley phantom images demonstrated clear energy-dependent contrast differences between the two threshold channels, with the low-threshold channel exhibiting higher contrast and lower noise due to its lower effective photon energy and higher photon counts. Quantitative analysis showed an image relative noise of 22% and a uniformity of 8%. Fine phantom structures were clearly resolved at 100 µm.

Conclusion

The tabletop PCD-CBCT system demonstrates robust performance within a fully integrated and automated workflow. This platform provides a foundation for future research in PCD-based CBCT.

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