{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T07:39:38Z","timestamp":1775029178852,"version":"3.50.1"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T00:00:00Z","timestamp":1738281600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T00:00:00Z","timestamp":1738281600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"National Science Foundation for Young Scientists of China","award":["61806060"],"award-info":[{"award-number":["61806060"]}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2021A1515220140"],"award-info":[{"award-number":["2021A1515220140"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Innovation Project of Sun Yat-sen University Cancer Center","award":["QNYCPY32"],"award-info":[{"award-number":["QNYCPY32"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1007\/s11760-024-03807-9","type":"journal-article","created":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T12:46:19Z","timestamp":1738327579000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["3D synthetic CT patch generation and reconstruction by using multi-resolution generative adversarial network"],"prefix":"10.1007","volume":"19","author":[{"given":"Liwei","family":"Deng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Songyu","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yufei","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sijuan","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,31]]},"reference":[{"issue":"2","key":"3807_CR1","doi-asserted-by":"publisher","first-page":"257","DOI":"10.2217\/nnm.11.190","volume":"7","author":"M Shilo","year":"2012","unstructured":"Shilo, M., Reuveni, T., Motiei, M., et al.: Nanoparticles as computed tomography contrast agents: current status and future perspectives. Nanomedicine, 7(2), 257\u2013269 (2012)","journal-title":"Nanomedicine"},{"key":"3807_CR2","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1007\/s00247-011-2099-y","volume":"41","author":"MJJPR Callahan","year":"2011","unstructured":"Callahan, M.J.J.P.R.: Ct dose reduction in practice. Pediatr. Radiol. 41, 488\u2013492 (2011)","journal-title":"Pediatr. Radiol."},{"issue":"4","key":"3807_CR3","doi-asserted-by":"publisher","first-page":"603","DOI":"10.1016\/j.jpedsurg.2006.12.009","volume":"42","author":"HE Rice","year":"2007","unstructured":"Rice, H.E., Frush, D.P., Farmer, D., et al.: Review of radiation risks from computed tomography: essentials for the pediatric surgeon. J. Pediatr. Surg. 42(4), 603\u2013607 (2007)","journal-title":"J. Pediatr. Surg."},{"issue":"2","key":"3807_CR4","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.meddos.2005.12.004","volume":"31","author":"L Xing","year":"2006","unstructured":"Xing, L., Thorndyke, B., Schreibmann, E., et al.: Overview of image-guided radiation therapy. Med. Dosim. 31(2), 91\u2013112 (2006)","journal-title":"Med. Dosim."},{"key":"3807_CR5","doi-asserted-by":"crossref","unstructured":"Abolaban, F.A.J.R.P.: Chemistry. Rev. Recent Impacts Artif. Intell. Radiat. Therapy Proced. 202, 110469 (2023)","DOI":"10.1016\/j.radphyschem.2022.110469"},{"key":"3807_CR6","doi-asserted-by":"crossref","unstructured":"Glide-Hurst, C.K., Lee, P., Yock, A.D. et al.: Adaptive radiation therapy (art) strategies and technical considerations: a state of the art review. Nrg. Oncol. 109(4), 1054\u20131075 (2021)","DOI":"10.1016\/j.ijrobp.2020.10.021"},{"key":"3807_CR7","doi-asserted-by":"crossref","unstructured":"Atiq, A., Atiq, M., Naeem, H. et al.: Modern radiation therapy techniques and their toxicities for breast cancer. In: Breast Cancer: From Bench to Personalized Medicine. Springer, p. 429\u2013451 (2022)","DOI":"10.1007\/978-981-19-0197-3_18"},{"issue":"5","key":"3807_CR8","doi-asserted-by":"publisher","first-page":"1337","DOI":"10.1016\/S0360-3016(02)02884-5","volume":"53","author":"DA Jaffray","year":"2002","unstructured":"Jaffray, D.A., Siewerdsen, J.H., Wong, J.W. et al.: Flat-panel cone-beam computed tomography for image-guided radiation therapy. Int. J. Radiat. Oncol. Biol. Physics. 53(5), 1337\u20131349 (2002)","journal-title":"Int. J. Radiat. Oncol. Biol. Physics."},{"issue":"5","key":"3807_CR9","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.1016\/j.ijrobp.2009.03.059","volume":"76","author":"RB Den","year":"2010","unstructured":"Den, R.B., Doemer, A., Kubicek, G. et al.: Daily image guidance with cone-beam computed tomography for head-and-neck cancer intensity-modulated radiotherapy: a prospective study. Int. J. Radiat. Oncol. Biol. Physics. 76(5), 1353\u20131359 (2010)","journal-title":"Int. J. Radiat. Oncol. Biol. Physics."},{"issue":"4","key":"3807_CR10","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1080\/0284186X.2017.1398414","volume":"57","author":"CA Hvid","year":"2018","unstructured":"Hvid, C.A., Elstr\u00f8m, U.V., Jensen, K. et al.: Cone-beam computed tomography (Cbct) for adaptive image guided head and neck radiation therapy. Acta Oncol. 57(4), 552\u2013556 (2018)","journal-title":"Acta Oncol."},{"issue":"1","key":"3807_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.adro.2019.07.013","volume":"5","author":"S Sajja","year":"2020","unstructured":"Sajja, S., Lee, Y., Eriksson, M. et al.: Technical principles of dual-energy cone beam computed tomography and clinical applications for radiation therapy. Adv. Radiat. oncol. 5(1), 1\u201316 (2020)","journal-title":"Adv. Radiat. oncol."},{"issue":"1","key":"3807_CR12","first-page":"100809","volume":"17","author":"Z Liang","year":"2024","unstructured":"Liang, Z., Wei, H., Liu, G. et al.: Leveraging gan-based Cbct-to-Ct translation models for enhanced image quality and accurate photon and proton dose calculation in adaptive radiotherapy. J. Radiat. Res. Appl. Sci. 17(1), 100809 (2024)","journal-title":"J. Radiat. Res. Appl. Sci."},{"issue":"1","key":"3807_CR13","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s13014-022-02191-3","volume":"18","author":"Y Chang","year":"2023","unstructured":"Chang, Y., Liang, Y., Yang, B., et al.: Dosimetric comparison of deformable image registration and synthetic ct generation based on Cbct images for organs at risk in cervical cancer radiotherapy. Radiat. Oncol. 18(1), 3 (2023)","journal-title":"Radiat. Oncol."},{"issue":"8","key":"3807_CR14","doi-asserted-by":"publisher","first-page":"5317","DOI":"10.1002\/mp.15684","volume":"49","author":"L Deng","year":"2022","unstructured":"Deng, L., Hu, J., Wang, J. et al.: Synthetic Ct generation based on Cbct using respath\u2010cyclegan. Med. phy. 49(8), 5317\u20135329 (2022)","journal-title":"Med. phy."},{"issue":"14","key":"3807_CR15","doi-asserted-by":"publisher","first-page":"145010","DOI":"10.1088\/1361-6560\/ac7b0a","volume":"67","author":"L Deng","year":"2022","unstructured":"Deng, L., Zhang, M., Wang, J. et al.: Improving cone-beam Ct quality using a cycle-residual connection with a dilated convolution-consistent generative adversarial network. Phys. Med. Biol. 67(14), 145010 (2022)","journal-title":"Phys. Med. Biol."},{"key":"3807_CR16","doi-asserted-by":"crossref","unstructured":"Zhu, J.-Y., Park, T., Isola, P. et al.: Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2223\u20132232 (2017)","DOI":"10.1109\/ICCV.2017.244"},{"issue":"6","key":"3807_CR17","doi-asserted-by":"publisher","first-page":"2472","DOI":"10.1002\/mp.14121","volume":"47","author":"Y Liu","year":"2020","unstructured":"Liu, Y., Lei, Y., Wang, T. et al.: Cbct\u2010based synthetic Ct generation using deep\u2010attention cyclegan for pancreatic adaptive radiotherapy. Med. phy. 47(6), 2472\u20132483 (2020)","journal-title":"Med. phy."},{"key":"3807_CR18","first-page":"106889","volume":"161","author":"L Deng","year":"2023","unstructured":"Deng, L., Ji, Y., Huang, S. et al.: Synthetic Ct generation from Cbct using double-chain-cyclegan. Comput. Biol. Med. 161, 106889 (2023)","journal-title":"Biol. Med."},{"key":"3807_CR19","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.J.A.: Denoising Diffusion probabilistic models. Adv. Neural Inf. Proces. Syst. 33, 6840\u20136851 (2020)","journal-title":"Adv. Neural Inf. Proces. Syst."},{"issue":"3","key":"3807_CR20","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1002\/mp.16704","volume":"51","author":"J Peng","year":"2024","unstructured":"Peng, J., Qiu, R.L., Wynne, J.F. et al.: Cbct\u2010based synthetic Ct image generation using conditional denoising diffusion probabilistic model. Med. Phy. 51(3), 1847\u20131859 (2024)","journal-title":"Med. Phy."},{"issue":"10","key":"3807_CR21","doi-asserted-by":"publisher","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","volume":"43","author":"J Wang","year":"2020","unstructured":"Wang, J., Sun, K., Cheng, T. et al.: Deep high-resolution representation learning for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3349\u20133364 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3807_CR22","doi-asserted-by":"crossref","unstructured":"Ding, X., Zhang, X., Han, J. et al.: Diverse branch block: building a convolution as an inception-like unit. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10886\u201310895 (2021)","DOI":"10.1109\/CVPR46437.2021.01074"},{"key":"3807_CR23","unstructured":"Lee, H.H., Bao, S., Huo, Y. et al.: 3D Ux-Net: a large Kernel volumetric convnet modernizing hierarchical transformer for medical image segmentation (2022)"},{"key":"3807_CR24","doi-asserted-by":"crossref","unstructured":"Liu, Z., Lin, Y., Cao, Y. et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10012\u201310022 (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"3807_CR25","doi-asserted-by":"publisher","first-page":"684","DOI":"10.1109\/TIP.2013.2293423","volume":"23","author":"W Xue","year":"2013","unstructured":"Xue, W., Zhang, L., Mou, X., et al.: Gradient magnitude similarity deviation: a highly efficient perceptual image quality index. IEEE Trans. Image Process. 23(2), 684\u2013695 (2013)","journal-title":"IEEE Trans. Image Process."}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03807-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-024-03807-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-024-03807-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T14:53:30Z","timestamp":1739458410000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-024-03807-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,31]]},"references-count":25,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["3807"],"URL":"https:\/\/doi.org\/10.1007\/s11760-024-03807-9","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,31]]},"assertion":[{"value":"16 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 December 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 January 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no relevant financial or non-financial interests to disclose.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The project was approved by the Ethics Committee of Sun Yat-sen University Cancer Centre, which waived informed consent.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Informed consent was obtained from all participants involved in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"267"}}