Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery
Conferences
Shu, X; Zhao, J; Lu, K; Ginn, J; Kim, Y; Yang, Z; Adamson, J; Mullikin, T; Wang, C
Published in: MEDICAL PHYSICS
October 2025
Duke Scholars
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Published In
MEDICAL PHYSICS
EISSN
2473-4209
ISSN
0094-2405
Publication Date
October 2025
Volume
52
Issue
10
Related Subject Headings
- Nuclear Medicine & Medical Imaging
- 5105 Medical and biological physics
- 4003 Biomedical engineering
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Shu, X., Zhao, J., Lu, K., Ginn, J., Kim, Y., Yang, Z., … Wang, C. (2025). Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery. In MEDICAL PHYSICS (Vol. 52).
Shu, X., J. Zhao, K. Lu, J. Ginn, Y. Kim, Z. Yang, J. Adamson, T. Mullikin, and C. Wang. “Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery.” In MEDICAL PHYSICS, Vol. 52, 2025.
Shu X, Zhao J, Lu K, Ginn J, Kim Y, Yang Z, et al. Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery. In: MEDICAL PHYSICS. 2025.
Shu, X., et al. “Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery.” MEDICAL PHYSICS, vol. 52, no. 10, 2025.
Shu X, Zhao J, Lu K, Ginn J, Kim Y, Yang Z, Adamson J, Mullikin T, Wang C. Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery. MEDICAL PHYSICS. 2025.
Published In
MEDICAL PHYSICS
EISSN
2473-4209
ISSN
0094-2405
Publication Date
October 2025
Volume
52
Issue
10
Related Subject Headings
- Nuclear Medicine & Medical Imaging
- 5105 Medical and biological physics
- 4003 Biomedical engineering