Multi-energy CT material decomposition using graph model improved CNN
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Biomedical Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11517-023-02986-w.pdf
Reference48 articles.
1. Bhayana R, Parakh A, Kambadakone A (2020) Material decomposition with dual-and multi-energy computed tomography. MRS Commun 10:558–565. https://doi.org/10.1557/mrc.2020.86
2. Franco PN, Spasiano CM, Maino C, De Ponti E, Ragusi M, Giandola T, Terrani S, Peroni M, Corso R, Ippolito D (2023) Principles and applications of dual-layer spectral CT in gastrointestinal imaging. Diagnostics 13:1740. https://doi.org/10.3390/diagnostics13101740
3. Wang S, Cai A, Wu W, Zhang T, Liu F, Yu H (2023) IMD-MTFC: image-domain material decomposition via material-image tensor factorization and clustering for spectral CT. IEEE Trans Radiation Plasma Med Sci 7:382–393. https://doi.org/10.1109/TRPMS.2023.3234613
4. Fang W, Wu DF, Kim K, Kalra MK, Singh R, Li L, Li QZ (2021) Iterative material decomposition for spectral CT using self-supervised Noise2Noise prior. Phys Med Biol 66. https://doi.org/10.1088/1361-6560/ac0afd
5. Geng MF, Tian ZF, Jiang Z, You YF, Feng XM, Xia Y, Yang K, Ren QS, Meng XX, Maier A et al (2021) PMS-GAN: parallel multi-stream generative adversarial network for multi-material decomposition in spectral computed tomography. IEEE Trans Med Imaging 40:571–584. https://doi.org/10.1109/TMI.2020.3031617
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