Dr. Chiara Lowe Profile

Dr. Chiara Lowe

at Univ of Canterbury

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Proceedings Article | 18 October 2022 Open Access

Motion correction via locally linear embedding for helical photon-counting CT

Mengzhou Li, Chiara Lowe, Anthony Butler, Phil Butler, Ge Wang

Proceedings Volume 12304, 123042I (2022) https://doi.org/10.1117/12.2646714

KEYWORDS: Motion estimation, Sensors, X-ray computed tomography, Reconstruction algorithms, Motion measurement, Photodetectors, Image quality, CT reconstruction, Image restoration, Computed tomography

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X-ray photon-counting detector (PCD) offers low noise, high resolution, and spectral characterization, representing a next generation of CT and enabling new biomedical applications. It is well known that involuntary patient motion may induce image artifacts with conventional CT scanning, and this problem becomes more serious with PCD due to its high detector pitch and extended scan time. Furthermore, PCD often comes with a substantial number of bad pixels, making analytic image reconstruction challenging and ruling out state-of-the-art motion correction methods that are based on analytical reconstruction. In this paper, we extend our previous locally linear embedding (LLE) cone-beam motion correction method to the helical scanning geometry, which is especially desirable given the high cost of large-area PCD. In addition to our adaption of LLE-based parametric searching to helical cone-beam photon-counting CT geometry, we introduce an unreliable-volume mask to improve the motion estimation accuracy and perform incremental updating on gradually refined sampling grids for optimization of both accuracy and efficiency. Our numerical results demonstrate that our method reduces the estimation errors near the two longitudinal ends of the reconstructed volume and overall image quality. The experimental results on clinical photon-counting scans of the patient extremities show significant resolution improvement after motion correction using our method, which reveals subtle fine structures previously hidden under motion blurring and artifacts.

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