Multi-layer enhancement of low-dose CT images via adaptive fusion
Author:
Funder
Natural Science Foundation of Xinjiang Province
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-022-02336-7.pdf
Reference29 articles.
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2. Purcell, L.N., et al.: Low-dose whole-body computed tomography and radiation exposure in patients with trauma—trust, but verify. JAMA Surg. 155(3), 232 (2020). https://doi.org/10.1001/jamasurg.2019.5469
3. Lee, H., Lee, J., et al.: Deep-neural-network based sinogram synthesis for sparse-view CT image reconstruction. IEEE Trans. Radiat. Plasma Med. Sci. 3, 109–119 (2018). https://doi.org/10.1109/trpms.2018.2867611
4. Ravenel, J.G., et al.: Radiation exposure and image quality in chest CT examinations. Ajr Am. J. Roentgenol. (2012). https://doi.org/10.2214/ajr.177.2.1770279
5. Gao, Y., et al.: A task-dependent investigation on dose and texture in CT image reconstruction. IEEE Trans. Radiat. Plasma Med. Sci. 4(4), 441–449 (2020). https://doi.org/10.1109/TRPMS.2019.2957459
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