Cyclic conditional diffusion models for CT-to-MR synthetic image segmentation with misaligned image pairs (vol 304, 130631, 2026)

초록

The authors regret to correct the Acknowledgments section: “The authors would like to thank the Advanced Medical Imaging Institute in the Department of Radiology, the Korea University Anam Hospital in the Republic of Korea and the researchers for providing software, datasets, and various forms of technical support. This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (no RS-2024-0033205, RS-2024-00338025, RS-2025-00558259); the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: RS-2022-KH129263); the Korea Medical Device Development Fund funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, Republic of Korea, the Ministry of Food and Drug Safety) (202011A02); by the Regional Innovation System & Education (RISE) through the Seoul RISE Center, funded by the Ministry of Education (MOE) and the Seoul Metropolitan Government (2025-RISE-01-014-05); and by a grant of Korea University Anam Hospital, Seoul, Republic of Korea (K2407931).” The authors apologise for any inconvenience caused. © 2026 The Author(s). Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.