Spectral-feature anisotropy-based spectral CT reconstruction

Zhaojun Yang; Li Zeng

doi:10.1117/12.3041170

10 September 2024 Spectral-feature anisotropy-based spectral CT reconstruction

Zhaojun Yang, Li Zeng

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 132570D (2024) https://doi.org/10.1117/12.3041170
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

The narrow energy bins of PCD-CT (Photon Counting Detector based Computed Tomography) make it hard to sufficiently collect incident photons. CT is performed at routine dose when dose constraint is met since relatively high doses of X-ray raise concerns about radiation risks. The above two points may both result in a Low-SNR (Low Signal-to-Noise Ratio) situation of projection data, leading noisy results. Besides, the SFA (spectral-feature anisotropy) exists in images corresponding different energy channels, it reflects the pixel saliency and spatial consistency of images related to different energy channels. The compatibility between mechanism of guided filter and the SFA prompted us to proposed a spectral CT reconstruction approach synergizing with both ADGF (Anisotropic Diffusion Guided Filter) and DAI (Dynamic Average Image) to reconstruct satisfying spectral CT image. ADGF was realized by fusing guided filter and anisotropic filter and was incorporated into the iterative process as a regularizer, making it more powerful in noise suppression while maintaining features. To further make full use of redundant information among different energy channels, DAI was utilized to induce channel-wise reconstruction. Experiments show that compared with results of other methods, ours achieve decent performance in visualization and quantitative indexes.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhaojun Yang and Li Zeng "Spectral-feature anisotropy-based spectral CT reconstruction", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 132570D (10 September 2024); https://doi.org/10.1117/12.3041170

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KEYWORDS

Tunable filters

Image processing

Anisotropic filtering

CT reconstruction

Image filtering

Anisotropic diffusion

Anisotropy

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