Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.
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| Title: | Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion. |
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| Authors: | You SH; Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Korea., Cho Y; Biomedical Research Center, Korea University College of Medicine, Seoul, Korea.; Department of Computer Science and Engineering, Soonchunhyang University, Asan-si, Korea., Kim B; Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Korea. bj1492.kim@gmail.com., Kim J; Department of Data Science, Korea University College of Informatics, Seoul, Korea., Im GJ; Department of Otorhinolaryngology-Head and Neck Surgery, Korea University College of Medicine, Seoul, Korea., Park E; Department of Otorhinolaryngology-Head and Neck Surgery, Korea University College of Medicine, Seoul, Korea., Kim I; Siemens Healthineers, Erlangen, Germany., Kim KM; Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Korea., Kim BK; Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, Korea. |
| Source: | European radiology [Eur Radiol] 2025 Jan; Vol. 35 (1), pp. 38-48. Date of Electronic Publication: 2024 Jul 18. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer International Country of Publication: Germany NLM ID: 9114774 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1432-1084 (Electronic) Linking ISSN: 09387994 NLM ISO Abbreviation: Eur Radiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1432-1084 |
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| DOI: | 10.1007/s00330-024-10967-2 |
