{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T10:55:19Z","timestamp":1768560919255,"version":"3.49.0"},"reference-count":70,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:00:00Z","timestamp":1758672000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62302345"],"award-info":[{"award-number":["62302345"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J. King Saud Univ. Comput. Inf. Sci."],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1007\/s44443-025-00200-5","type":"journal-article","created":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T10:45:49Z","timestamp":1758710749000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Source-free cross-modality medical image synthesis with diffusion priors"],"prefix":"10.1007","volume":"37","author":[{"given":"Jia","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3349-5161","authenticated-orcid":false,"given":"Jun","family":"Bai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kai","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinrong","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,24]]},"reference":[{"key":"200_CR1","unstructured":"Alexey D (2020) An image is worth 16x16 words: transformers for image recognition at scale. arXiv: 2010.11929"},{"key":"200_CR2","doi-asserted-by":"publisher","first-page":"101960","DOI":"10.1016\/j.media.2021.101960","volume":"69","author":"I Alnazer","year":"2021","unstructured":"Alnazer I, Bourdon P, Urruty T, Falou O, Khalil M, Shahin A, Fernandez-Maloigne C (2021) Recent advances in medical image processing for the evaluation of chronic kidney disease. Med Image Anal 69:101960","journal-title":"Med Image Anal"},{"key":"200_CR3","doi-asserted-by":"crossref","unstructured":"Arslan F, Kabas B, Dalmaz O, Ozbey M, \u00c7ukur T (2024) Self-consistent recursive diffusion bridge for medical image translation. arXiv:2405.06789","DOI":"10.1016\/j.media.2025.103747"},{"key":"200_CR4","unstructured":"Atli OF, Kabas B, Arslan F, Yurt M, Dalmaz O, \u00c7ukur T (2024) I2i-mamba: multi-modal medical image synthesis via selective state space modeling. arXiv:2405.14022"},{"key":"200_CR5","doi-asserted-by":"crossref","unstructured":"Bowles C, Qin C, Ledig C, Guerrero R, Gunn R, Hammers A, Sakka E, Dickie DA, Hern\u00e1ndez MV, Royle N et al (2016) Pseudo-healthy image synthesis for white matter lesion segmentation. In: Proceedings of the international conference on medical image computing and computer-assisted intervention. Springer, pp 87\u201396","DOI":"10.1007\/978-3-319-46630-9_9"},{"key":"200_CR6","doi-asserted-by":"publisher","first-page":"102699","DOI":"10.1016\/j.media.2022.102699","volume":"84","author":"D Chalap","year":"2023","unstructured":"Chalap D et al (2023) Domain generalization for medical imaging: a survey. Med Image Anal 84:102699. https:\/\/doi.org\/10.1016\/j.media.2022.102699","journal-title":"Med Image Anal"},{"issue":"3","key":"200_CR7","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1109\/TMI.2017.2764326","volume":"37","author":"A Chartsias","year":"2017","unstructured":"Chartsias A, Joyce T, Giuffrida MV, Tsaftaris SA (2017) Multimodal mr synthesis via modality-invariant latent representation. IEEE Trans Med Imaging 37(3):803\u2013814","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR8","doi-asserted-by":"publisher","unstructured":"Chartsias A, Joyce T, Papanastasiou G, Williams M, Newby D, Dharmakumar R, Tsaftaris SA (2019) Factorised representation learning in medical imaging. In: Proceedings of the international conference on medical image computing and computer-assisted intervention. Lecture Notes in Computer Science, vol 11766. Springer, ???, pp 743\u2013751. https:\/\/doi.org\/10.1007\/978-3-030-32239-7_82","DOI":"10.1007\/978-3-030-32239-7_82"},{"key":"200_CR9","doi-asserted-by":"publisher","first-page":"16010","DOI":"10.1109\/ACCESS.2021.3053212","volume":"9","author":"J Chen","year":"2021","unstructured":"Chen J, Liu Y, Wei S, Bian Z, Subramanian S, Carass A, Prince JL, Du Y (2021) Cross-modality neuroimage synthesis: a survey. IEEE Access 9:16010\u201316033. https:\/\/doi.org\/10.1109\/ACCESS.2021.3053212","journal-title":"IEEE Access"},{"key":"200_CR10","unstructured":"Choi JW, Lee SW (2022) Brain pet synthesis from mri using generative adversarial network for multi-modal alzheimer\u2019s disease diagnosis. Comput Methods Programs Biomed"},{"issue":"12","key":"200_CR11","doi-asserted-by":"publisher","first-page":"2598","DOI":"10.1109\/TMI.2016.2589760","volume":"35","author":"N Cordier","year":"2016","unstructured":"Cordier N, Delingette H, L\u00ea M, Ayache N (2016) Extended modality propagation: image synthesis of pathological cases. IEEE Trans Med Imaging 35(12):2598\u20132608","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"200_CR12","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1109\/TMI.2017.2759102","volume":"37","author":"P Costa","year":"2017","unstructured":"Costa P, Galdran A, Meyer MI, Niemeijer M, Abr\u00e0moff M, Mendon\u00e7a AM, Campilho A (2017) End-to-end adversarial retinal image synthesis. IEEE Trans Med Imaging 37(3):781\u2013791","journal-title":"IEEE Trans Med Imaging"},{"issue":"10","key":"200_CR13","doi-asserted-by":"publisher","first-page":"2598","DOI":"10.1109\/TMI.2022.3167808","volume":"41","author":"O Dalmaz","year":"2022","unstructured":"Dalmaz O, Yurt M, \u00c7ukur T (2022) Resvit: residual vision transformers for multimodal medical image synthesis. IEEE Trans Med Imaging 41(10):2598\u20132614","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR14","doi-asserted-by":"crossref","unstructured":"Deng J, Dong W, Socher R, Li L-J, Li K, Fei-Fei L (2009) Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. Ieee, pp 248\u2013255","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"200_CR15","first-page":"8780","volume":"34","author":"P Dhariwal","year":"2021","unstructured":"Dhariwal P, Nichol A (2021) Diffusion models beat gans on image synthesis. Adv Neural Inf Process Syst 34:8780\u20138794","journal-title":"Adv Neural Inf Process Syst"},{"issue":"11","key":"200_CR16","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2020) Generative adversarial networks. Commun ACM 63(11):139\u2013144","journal-title":"Commun ACM"},{"issue":"3","key":"200_CR17","doi-asserted-by":"publisher","first-page":"1173","DOI":"10.1109\/TBME.2021.3117407","volume":"69","author":"H Guan","year":"2021","unstructured":"Guan H, Liu M (2021) Domain adaptation for medical image analysis: a survey. IEEE Trans Biomed Eng 69(3):1173\u20131185","journal-title":"IEEE Trans Biomed Eng"},{"key":"200_CR18","unstructured":"Gu A, Dao T (2023) Mamba: linear-time sequence modeling with selective state spaces. arXiv:2312.00752"},{"key":"200_CR19","unstructured":"Heusel M, Ramsauer H, Unterthiner T, Nessler B, Hochreiter S (2017) Gans trained by a two time-scale update rule converge to a local nash equilibrium. Adv Neural Inf Process Syst 30"},{"key":"200_CR20","doi-asserted-by":"publisher","unstructured":"Hiasa Y, Otake Y, Takao M, Matsuoka T, Takashima K, Carass A, Prince JL, Sugano N, Sato Y (2018) Cross-modality image synthesis from unpaired data using cyclegan: effects of gradient consistency loss and training data size. In: Goksel O, Oguz I, Gooya A, Burgos N (eds) Proceedings of the international conference on medical image computing and computer-assisted intervention. Lecture Notes in Computer Science, vol 11037. Springer, ???, pp 31\u201341. https:\/\/doi.org\/10.1007\/978-3-030-00536-8_4","DOI":"10.1007\/978-3-030-00536-8_4"},{"key":"200_CR21","first-page":"6840","volume":"33","author":"J Ho","year":"2020","unstructured":"Ho J, Jain A, Abbeel P (2020) Denoising diffusion probabilistic models. Adv Neural Inf Process Syst 33:6840\u20136851","journal-title":"Adv Neural Inf Process Syst"},{"key":"200_CR22","doi-asserted-by":"publisher","first-page":"102940","DOI":"10.1016\/j.media.2023.102940","volume":"90","author":"J Honkamaa","year":"2023","unstructured":"Honkamaa J, Khan U, Koivukoski S, Valkonen M, Latonen L, Ruusuvuori P, Marttinen P (2023) Deformation equivariant cross-modality image synthesis with paired non-aligned training data. Med Image Anal 90:102940","journal-title":"Med Image Anal"},{"key":"200_CR23","doi-asserted-by":"publisher","first-page":"101967","DOI":"10.1016\/j.media.2021.101967","volume":"69","author":"CM Hyun","year":"2021","unstructured":"Hyun CM, Baek SH, Lee M, Lee SM, Seo JK (2021) Deep learning-based solvability of underdetermined inverse problems in medical imaging. Med Image Anal 69:101967","journal-title":"Med Image Anal"},{"key":"200_CR24","doi-asserted-by":"crossref","unstructured":"Iacono P, Khan N (2023) Structure preserving cycle-gan for unsupervised medical image domain adaptation. arXiv:2304.09164","DOI":"10.32920\/22734377"},{"key":"200_CR25","unstructured":"IXI Consortium (n.d.) IXI Dataset. http:\/\/brain-development.org\/ixi-dataset\/. Information eXtraction from Images (EPSRC GR\/S21533\/02)"},{"key":"200_CR26","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/j.inffus.2021.02.012","volume":"73","author":"X Jiang","year":"2021","unstructured":"Jiang X, Ma J, Xiao G, Shao Z, Guo X (2021) A review of multimodal image matching: methods and applications. Inf Fusion 73:22\u201371","journal-title":"Inf Fusion"},{"key":"200_CR27","doi-asserted-by":"crossref","unstructured":"Jiang L, Mao Y, Wang X, Chen X, Li C (2023) Cola-diff: conditional latent diffusion model for multi-modal mri synthesis. In: Proceedings of the international conference on medical image computing and computer-assisted intervention. Springer, pp 398\u2013408","DOI":"10.1007\/978-3-031-43999-5_38"},{"issue":"12","key":"200_CR28","doi-asserted-by":"publisher","first-page":"4413","DOI":"10.1109\/TMI.2020.3018560","volume":"39","author":"J Jiao","year":"2020","unstructured":"Jiao J, Namburete AI, Papageorghiou AT, Noble JA (2020) Self-supervised ultrasound to mri fetal brain image synthesis. IEEE Trans Med Imaging 39(12):4413\u20134424","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR29","doi-asserted-by":"publisher","first-page":"4509","DOI":"10.1109\/TIP.2017.2713099","volume":"26","author":"KH Jin","year":"2016","unstructured":"Jin KH, McCann MT, Froustey E, Unser MA (2016) Deep convolutional neural network for inverse problems in imaging. IEEE Trans Image Process 26:4509\u20134522","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"200_CR30","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1038\/s42256-020-0186-1","volume":"2","author":"GA Kaissis","year":"2020","unstructured":"Kaissis GA, Makowski MR, Ruckert D, Braren RF (2020) Secure, privacy-preserving and federated machine learning in medical imaging. Nature Mach Intell 2(6):305\u2013311. https:\/\/doi.org\/10.1038\/s42256-020-0186-1","journal-title":"Nature Mach Intell"},{"key":"200_CR31","doi-asserted-by":"publisher","first-page":"101907","DOI":"10.1016\/j.media.2020.101907","volume":"68","author":"N Karani","year":"2021","unstructured":"Karani N, Erdil E, Chaitanya K, Konukoglu E (2021) Test-time adaptable neural networks for robust medical image segmentation. Med Image Anal 68:101907. https:\/\/doi.org\/10.1016\/j.media.2020.101907","journal-title":"Med Image Anal"},{"key":"200_CR32","first-page":"23593","volume":"35","author":"B Kawar","year":"2022","unstructured":"Kawar B, Elad M, Ermon S, Song J (2022) Denoising diffusion restoration models. Adv Neural Inf Process Syst 35:23593\u201323606","journal-title":"Adv Neural Inf Process Syst"},{"issue":"5","key":"200_CR33","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10916-020-01550-5","volume":"44","author":"J Lee","year":"2020","unstructured":"Lee J et al (2020) Limitations of medical data sharing across institutions. J Med Syst 44(5):1\u201310. https:\/\/doi.org\/10.1007\/s10916-020-01550-5","journal-title":"J Med Syst"},{"key":"200_CR34","doi-asserted-by":"publisher","first-page":"102461","DOI":"10.1016\/j.media.2022.102461","volume":"79","author":"J Liang","year":"2022","unstructured":"Liang J, Yang X, Huang Y, Li H, He S, Hu X, Chen Z, Xue W, Cheng J, Ni D (2022) Sketch guided and progressive growing gan for realistic and editable ultrasound image synthesis. Med Image Anal 79:102461","journal-title":"Med Image Anal"},{"key":"200_CR35","doi-asserted-by":"crossref","unstructured":"Li Y, Shao H-C, Liang X, Chen L, Li R, Jiang S, Wang J, Zhang Y (2023) Zero-shot medical image translation via frequency-guided diffusion models. IEEE Trans Med Imag (2023)","DOI":"10.1109\/TMI.2023.3325703"},{"key":"200_CR36","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s11747-016-0495-4","volume":"45","author":"KD Martin","year":"2017","unstructured":"Martin KD, Murphy PE (2017) The role of data privacy in marketing. J Acad Mark Sci 45:135\u2013155","journal-title":"J Acad Mark Sci"},{"key":"200_CR37","doi-asserted-by":"publisher","first-page":"104336","DOI":"10.1016\/j.jbi.2023.104336","volume":"136","author":"CS Mendoza","year":"2023","unstructured":"Mendoza CS et al (2023) A survey on generalization in deep learning for medical imaging. J Biomed Inf 136:104336. https:\/\/doi.org\/10.1016\/j.jbi.2023.104336","journal-title":"J Biomed Inf"},{"issue":"3","key":"200_CR38","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2013","unstructured":"Mittal A, Soundararajan R, Bovik AC (2013) Making a \u201ccompletely blind\u2019\u2019 image quality analyzer. IEEE Signal Process Lett 20(3):209\u2013212. https:\/\/doi.org\/10.1109\/LSP.2012.2227726","journal-title":"IEEE Signal Process Lett"},{"key":"200_CR39","doi-asserted-by":"crossref","unstructured":"\u00d6zbey M, Dalmaz O, Dar SU, Bedel HA, \u00d6zturk \u015e, G\u00fcng\u00f6r A, \u00c7ukur T (2023) Unsupervised medical image translation with adversarial diffusion models. IEEE Trans Med Imag","DOI":"10.1109\/TMI.2023.3290149"},{"key":"200_CR40","doi-asserted-by":"crossref","unstructured":"Patro BN, Agneeswaran VS (2024) Mamba-360: Survey of state space models as transformer alternative for long sequence modelling: methods, applications, and challenges. arXiv:2404.16112","DOI":"10.2139\/ssrn.4930035"},{"key":"200_CR41","doi-asserted-by":"crossref","unstructured":"Roy S, Chou Y-Y, Jog A, Butman JA, Pham DL (2016) Patch based synthesis of whole head mr images: application to epi distortion correction. In: Proceedings of the international conference on medical image computing and computer-assisted intervention. Springer, pp 146\u2013156","DOI":"10.1007\/978-3-319-46630-9_15"},{"key":"200_CR42","doi-asserted-by":"crossref","unstructured":"Sevetlidis V, Giuffrida MV, Tsaftaris SA (2016) Whole image synthesis using a deep encoder-decoder network. In: Proceedings of the international conference on medical image computing and computer-assisted intervention. Springer, pp 127\u2013137","DOI":"10.1007\/978-3-319-46630-9_13"},{"key":"200_CR43","unstructured":"Song J, Meng C, Ermon S (2020) Denoising diffusion implicit models. arXiv:2010.02502"},{"key":"200_CR44","unstructured":"Song Y, Sohl-Dickstein J, Kingma DP, Kumar A, Ermon S, Poole B (2020) Score-based generative modeling through stochastic differential equations. arXiv:2011.13456"},{"key":"200_CR45","unstructured":"Su X, Song J, Meng C, Ermon S (2022) Dual diffusion implicit bridges for image-to-image translation. arXiv:2203.08382"},{"key":"200_CR46","doi-asserted-by":"publisher","first-page":"16010","DOI":"10.1109\/ACCESS.2021.3053212","volume":"9","author":"C Tanner","year":"2021","unstructured":"Tanner C et al (2021) Challenges and open issues in medical image registration. IEEE Access 9:16010\u201316033. https:\/\/doi.org\/10.1109\/ACCESS.2021.3053212","journal-title":"IEEE Access"},{"issue":"7","key":"200_CR47","doi-asserted-by":"publisher","first-page":"4664","DOI":"10.1002\/mp.16529","volume":"50","author":"A Thummerer","year":"2023","unstructured":"Thummerer A, Bijl E, Galapon A Jr, Verhoeff JJ, Langendijk JA, Both S, Berg CNA, Maspero M (2023) Synthrad 2023 grand challenge dataset: generating synthetic ct for radiotherapy. Med Phys 50(7):4664\u20134674","journal-title":"Med Phys"},{"issue":"4","key":"200_CR48","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"200_CR49","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.inffus.2020.10.015","volume":"67","author":"C Wang","year":"2021","unstructured":"Wang C, Yang G, Papanastasiou G, Tsaftaris SA, Newby DE, Gray C, Macnaught G, MacGillivray TJ (2021) Dicyc: gan-based deformation invariant cross-domain information fusion for medical image synthesis. Inf Fusion 67:147\u2013160","journal-title":"Inf Fusion"},{"issue":"2","key":"200_CR50","doi-asserted-by":"publisher","first-page":"222471","DOI":"10.1148\/radiol.222471","volume":"308","author":"B Wang","year":"2023","unstructured":"Wang B, Pan Y, Xu S, Zhang Y, Ming Y, Chen L, Liu X, Wang C, Liu Y, Xia Y (2023) Quantitative cerebral blood volume image synthesis from standard mri using image-to-image translation for brain tumors. Radiology 308(2):222471","journal-title":"Radiology"},{"issue":"11","key":"200_CR51","doi-asserted-by":"publisher","first-page":"3362","DOI":"10.1109\/TMI.2023.3283948","volume":"42","author":"CJ Wang","year":"2023","unstructured":"Wang CJ, Rost NS, Golland P (2023) Spatial-intensity transforms for medical image-to-image translation. IEEE Trans Med Imaging 42(11):3362\u20133373","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR52","doi-asserted-by":"crossref","unstructured":"Wang Z, Yang Y, Chen Y, Yuan T, Sermesant M, Delingette H, Wu O (2024) Mutual information guided diffusion for zero-shot cross-modality medical image translation. IEEE Trans Med Imag","DOI":"10.1109\/TMI.2024.3382043"},{"key":"200_CR53","doi-asserted-by":"publisher","unstructured":"Wu S, Chen Y, Mermet S, Hurni L, Schindler K, Gonthier N, Landrieu L (2024) Stegogan: leveraging steganography for non-bijective image-to-image translation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, Seattle, WA, USA, pp 7922\u20137931. https:\/\/doi.org\/10.1109\/CVPR52733.2024.00757","DOI":"10.1109\/CVPR52733.2024.00757"},{"key":"200_CR54","doi-asserted-by":"publisher","unstructured":"Xia Y, Yang D, Yu Z, Liu F, Cai J, Yu L, Zhu Z, Xu D, Yuille A, Roth H (2020) Uncertainty-aware multi-view co-training for semi-supervised medical image segmentation and domain adaptation. Med Image Anal 65:101766. https:\/\/doi.org\/10.1016\/j.media.2020.101766","DOI":"10.1016\/j.media.2020.101766"},{"issue":"12","key":"200_CR55","doi-asserted-by":"publisher","first-page":"4249","DOI":"10.1109\/TMI.2020.3015379","volume":"39","author":"H Yang","year":"2020","unstructured":"Yang H, Sun J, Carass A, Zhao C, Lee J, Prince JL, Xu Z (2020) Unsupervised mr-to-ct synthesis using structure-constrained cyclegan. IEEE Trans Med Imaging 39(12):4249\u20134261. https:\/\/doi.org\/10.1109\/TMI.2020.3015379","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR56","doi-asserted-by":"crossref","unstructured":"Ye\u011fin MN, Amasyal\u0131 MF (2024) Theoretical research on generative diffusion models: an overview. arXiv:2404.09016","DOI":"10.2139\/ssrn.4627329"},{"key":"200_CR57","unstructured":"Yoon JS, Oh K, Shin Y, Mazurowski MA, Suk H-I (2023) Domain generalization for medical image analysis: a survey. arXiv:2310.08598"},{"issue":"7","key":"200_CR58","doi-asserted-by":"publisher","first-page":"1750","DOI":"10.1109\/TMI.2019.2895894","volume":"38","author":"B Yu","year":"2019","unstructured":"Yu B, Zhou L, Wang L, Shi Y, Fripp J, Bourgeat P (2019) Ea-gans: edge-aware generative adversarial networks for cross-modality mr image synthesis. IEEE Trans Med Imaging 38(7):1750\u20131762","journal-title":"IEEE Trans Med Imaging"},{"issue":"7","key":"200_CR59","doi-asserted-by":"publisher","first-page":"2339","DOI":"10.1109\/TMI.2020.2969630","volume":"39","author":"B Yu","year":"2020","unstructured":"Yu B, Zhou L, Wang L, Shi Y, Fripp J, Bourgeat P (2020) Sample-adaptive gans: linking global and local mappings for cross-modality mr image synthesis. IEEE Trans Med Imaging 39(7):2339\u20132350","journal-title":"IEEE Trans Med Imaging"},{"key":"200_CR60","doi-asserted-by":"crossref","unstructured":"Yurt M, Dar SU, Erdem A, Erdem E, Oguz KK, \u00c7ukur T (2021) mustgan: multi-stream generative adversarial networks for mr image synthesis. Med Image Anal 70:101944","DOI":"10.1016\/j.media.2020.101944"},{"key":"200_CR61","doi-asserted-by":"crossref","unstructured":"Zhang H, Xu T, Li H, Zhang S, Wang X, Huang X, Metaxas DN (2017) Stackgan++: realistic image synthesis with stacked generative adversarial networks. IEEE Trans Pattern Anal Mach Intell 41:1947\u20131962","DOI":"10.1109\/TPAMI.2018.2856256"},{"key":"200_CR62","doi-asserted-by":"publisher","first-page":"101832","DOI":"10.1016\/j.media.2020.101832","volume":"67","author":"L Zhang","year":"2021","unstructured":"Zhang L, Wang X, Yang D, Sanford T, Harmon S, Turkbey B, Roth H, Myronenko A, Xu D, Xu Z (2021) Generalizing deep learning for medical image segmentation to unseen domains via deep stacked transformation. Med Image Anal 67:101832. https:\/\/doi.org\/10.1016\/j.media.2020.101832","journal-title":"Med Image Anal"},{"key":"200_CR63","unstructured":"Zhang H, Goodfellow I, Metaxas D, Odena A (2019) Self-attention generative adversarial networks. In: Proceedings of the international conference on machine learning. Proceedings of machine learning research, vol 97, pp 7354\u20137363"},{"key":"200_CR64","doi-asserted-by":"crossref","unstructured":"Zhang R, Isola P, Efros AA, Shechtman E, Wang O (2018) The unreasonable effectiveness of deep features as a perceptual metric. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 586\u2013595","DOI":"10.1109\/CVPR.2018.00068"},{"key":"200_CR65","doi-asserted-by":"crossref","unstructured":"Zhan C, Lin Y, Wang G, Wang H, Wu J (2024) Medm2g: unifying medical multi-modal generation via cross-guided diffusion with visual invariant. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 11502\u201311512","DOI":"10.1109\/CVPR52733.2024.01093"},{"key":"200_CR66","doi-asserted-by":"publisher","first-page":"102102","DOI":"10.1016\/j.media.2021.102102","volume":"72","author":"A Zhao","year":"2022","unstructured":"Zhao A et al (2022) A survey on deep learning-based medical image synthesis. Med Image Anal 72:102102. https:\/\/doi.org\/10.1016\/j.media.2021.102102","journal-title":"Med Image Anal"},{"issue":"9","key":"200_CR67","doi-asserted-by":"publisher","first-page":"2772","DOI":"10.1109\/TMI.2020.2975344","volume":"39","author":"T Zhou","year":"2020","unstructured":"Zhou T, Fu H, Chen G, Shen J, Shao L (2020) Hi-net: hybrid-fusion network for multi-modal mr image synthesis. IEEE Trans Med Imaging 39(9):2772\u20132781","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"200_CR68","doi-asserted-by":"publisher","first-page":"820","DOI":"10.1109\/JPROC.2021.3054390","volume":"109","author":"SK Zhou","year":"2021","unstructured":"Zhou SK, Greenspan H, Davatzikos C, Duncan JS, Van Ginneken B, Madabhushi A, Prince JL, Rueckert D, Summers RM (2021) A review of deep learning in medical imaging: imaging traits, technology trends, case studies with progress highlights, and future promises. Proc IEEE 109(5):820\u2013838","journal-title":"Proc IEEE"},{"issue":"1","key":"200_CR69","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/JBHI.2020.3045475","volume":"26","author":"Y Zhou","year":"2022","unstructured":"Zhou Y, Wang B, He X, Cui S, Shao L (2022) Dr-gan: conditional generative adversarial network for fine-grained lesion synthesis on diabetic retinopathy images. IEEE J Biomed Health Inform 26(1):56\u201366. https:\/\/doi.org\/10.1109\/JBHI.2020.3045475","journal-title":"IEEE J Biomed Health Inform"},{"key":"200_CR70","doi-asserted-by":"publisher","unstructured":"Zhu J-Y, Park T, Isola P, Efros AA (2017) Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE international conference on computer vision, pp 2242\u20132251. https:\/\/doi.org\/10.1109\/ICCV.2017.244","DOI":"10.1109\/ICCV.2017.244"}],"container-title":["Journal of King Saud University Computer and Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00200-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s44443-025-00200-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s44443-025-00200-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T15:36:23Z","timestamp":1761752183000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s44443-025-00200-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,24]]},"references-count":70,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2025,10]]}},"alternative-id":["200"],"URL":"https:\/\/doi.org\/10.1007\/s44443-025-00200-5","relation":{},"ISSN":["1319-1578","2213-1248"],"issn-type":[{"value":"1319-1578","type":"print"},{"value":"2213-1248","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,24]]},"assertion":[{"value":"14 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2025","order":3,"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 competing interests to declare.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"214"}}