Reconstruction of local noise power spectrum from a single CT data acquisition

Chengzhu Zhang; Ke Li; Ran Zhang; Guang-Hong Chen

doi:10.1117/12.2654367

7 April 2023 Reconstruction of local noise power spectrum from a single CT data acquisition

Chengzhu Zhang, Ke Li, Ran Zhang, Guang-Hong Chen

Proceedings Volume 12463, Medical Imaging 2023: Physics of Medical Imaging; 124633U (2023) https://doi.org/10.1117/12.2654367
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Noise power spectrum (NPS) is an indispensable component in the quantitative assessment of x-ray computed tomography (CT) image quality. In principle, an accurate experimental measurement of the NPS in CT requires many repeated CT image acquisitions under the same conditions. Repeated CT scanning of the same human subject is not feasible due to the obvious ethical and safety concerns associated with the increased radiation exposure. Alternatively, the NPS can be estimated using conventional phantom-based methods via repeated measurements. However, phantom-derived results 1) do not necessarily represent the patient-specific noise characteristics of CT images and 2) do not show local NPS concerning a very small region either. Therefore, it is highly desirable to directly estimate the local NPS directly from patient CT data without resolving to repeated measurements. In this work, a fast and highly accurate one-sample approach was proposed to enable patient-specific local NPS measurement with respect to a single pixel from a single CT data acquisition. In numerical studies, the one-sample approach was superior compared to the conventional multi-sample approach with 50,000 repeated measurements.

Citation Download Citation

Chengzhu Zhang, Ke Li, Ran Zhang, and Guang-Hong Chen "Reconstruction of local noise power spectrum from a single CT data acquisition", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 124633U (7 April 2023); https://doi.org/10.1117/12.2654367

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