{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T09:50:37Z","timestamp":1758361837631,"version":"3.44.0"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032053244"},{"type":"electronic","value":"9783032053251"}],"license":[{"start":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T00:00:00Z","timestamp":1758326400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,20]],"date-time":"2025-09-20T00:00:00Z","timestamp":1758326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-05325-1_45","type":"book-chapter","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T19:06:09Z","timestamp":1758308769000},"page":"470-480","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["RetinaLogos: Fine-Grained Synthesis of\u00a0High-Resolution Retinal Images Through Captions"],"prefix":"10.1007","author":[{"given":"Junzhi","family":"Ning","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kaijing","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diping","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huihui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanzhou","family":"Su","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianbin","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiyao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Ye","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanfeng","family":"Ji","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junjun","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,20]]},"reference":[{"issue":"1","key":"45_CR1","doi-asserted-by":"publisher","first-page":"60","DOI":"10.3390\/electronics11010060","volume":"11","author":"P Andreini","year":"2021","unstructured":"Andreini, P., et al.: A two-stage gan for high-resolution retinal image generation and segmentation. Electronics 11(1), 60 (2021)","journal-title":"Electronics"},{"key":"45_CR2","unstructured":"Bluethgen, C., et al.: A vision\u2013language foundation model for the generation of realistic chest x-ray images. Nat. Biomed. Eng. 1\u201313 (2024)"},{"issue":"1","key":"45_CR3","doi-asserted-by":"publisher","first-page":"542","DOI":"10.1109\/TMI.2023.3313786","volume":"43","author":"C Vente","year":"2023","unstructured":"Vente, C., et al.: Airogs: artificial intelligence for robust glaucoma screening challenge. IEEE Trans. Med. Imaging 43(1), 542\u2013557 (2023)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"45_CR4","doi-asserted-by":"crossref","unstructured":"Demmin, D.L., Silverstein, S.M.: Visual impairment and mental health: unmet needs and treatment options. Clin. Ophthalmol. 4229\u20134251 (2020)","DOI":"10.2147\/OPTH.S258783"},{"key":"45_CR5","doi-asserted-by":"publisher","unstructured":"Du, J., et al.: Ret-clip: a retinal image foundation model pre-trained with clinical diagnostic reports. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 709\u2013719. Springer, Heidelberg (2024). https:\/\/doi.org\/10.1007\/978-3-031-72390-2_66","DOI":"10.1007\/978-3-031-72390-2_66"},{"key":"45_CR6","unstructured":"Fang, H., et\u00a0al.: Refuge2 challenge: a treasure trove for multi-dimension analysis and evaluation in glaucoma screening. arXiv preprint arXiv:2202.08994 (2022)"},{"key":"45_CR7","unstructured":"Gao, P., et\u00a0al.: Lumina-t2x: transforming text into any modality, resolution, and duration via flow-based large diffusion transformers. arXiv preprint arXiv:2405.05945 (2024)"},{"key":"45_CR8","doi-asserted-by":"crossref","unstructured":"Go, S., Ji, Y., Park, S.J., Lee, S.: Generation of structurally realistic retinal fundus images with diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 2335\u20132344 (2024)","DOI":"10.1109\/CVPRW63382.2024.00239"},{"key":"45_CR9","doi-asserted-by":"crossref","unstructured":"Gulshan, V., et\u00a0al.: Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316(22), 2402\u20132410 (2016)","DOI":"10.1001\/jama.2016.17216"},{"issue":"1","key":"45_CR10","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1186\/s40708-020-00104-2","volume":"7","author":"J Islam","year":"2020","unstructured":"Islam, J., Zhang, Y.: Gan-based synthetic brain pet image generation. Brain Inf. 7(1), 3 (2020)","journal-title":"Brain Inf."},{"issue":"2","key":"45_CR11","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1109\/JBHI.2020.3042523","volume":"25","author":"Y Jiang","year":"2020","unstructured":"Jiang, Y., Chen, H., Loew, M., Ko, H.: Covid-19 ct image synthesis with a conditional generative adversarial network. IEEE J. Biomed. Health Inform. 25(2), 441\u2013452 (2020)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"45_CR12","unstructured":"Karthik, M., Dane, S.: Aptos 2019 blindness detection. Kaggle https:\/\/kaggle.com\/competitions\/aptos2019-blindness-detection Go to reference in p.\u00a05 (2019)"},{"issue":"1","key":"45_CR13","doi-asserted-by":"publisher","first-page":"17307","DOI":"10.1038\/s41598-022-20698-3","volume":"12","author":"M Kim","year":"2022","unstructured":"Kim, M., et al.: Synthesizing realistic high-resolution retina image by style-based generative adversarial network and its utilization. Sci. Rep. 12(1), 17307 (2022)","journal-title":"Sci. Rep."},{"issue":"9072","key":"45_CR14","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/S0140-6736(97)04195-0","volume":"350","author":"R Klein","year":"1997","unstructured":"Klein, R., Klein, B.E.: Diabetic eye disease. Lancet 350(9072), 197\u2013204 (1997)","journal-title":"Lancet"},{"key":"45_CR15","unstructured":"Li, W., et al.: Ophora: a large-scale data-driven text-guided ophthalmic surgical video generation model. arXiv preprint arXiv:2505.07449 (2025)"},{"issue":"1","key":"45_CR16","doi-asserted-by":"publisher","first-page":"12098","DOI":"10.1038\/s41598-023-39278-0","volume":"13","author":"G M\u00fcller-Franzes","year":"2023","unstructured":"M\u00fcller-Franzes, G., et al.: A multimodal comparison of latent denoising diffusion probabilistic models and generative adversarial networks for medical image synthesis. Sci. Rep. 13(1), 12098 (2023)","journal-title":"Sci. Rep."},{"key":"45_CR17","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.patrec.2025.03.033","volume":"193","author":"J Ning","year":"2025","unstructured":"Ning, J., et al.: Unpaired translation of chest x-ray images for lung opacity diagnosis via adaptive activation masks and cross-domain alignment. Pattern Recogn. Lett. 193, 21\u201328 (2025)","journal-title":"Pattern Recogn. Lett."},{"key":"45_CR18","doi-asserted-by":"crossref","unstructured":"Ning, J., Xing, X., Zhang, S., Ma, X., Yang, G.: Unveiling the capabilities of latent diffusion models for classification of lung diseases in chest x-rays. In: 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), pp.\u00a01\u20135. IEEE (2025)","DOI":"10.1109\/ISBI60581.2025.10981008"},{"issue":"1","key":"45_CR19","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/JBHI.2021.3110593","volume":"26","author":"Y Niu","year":"2021","unstructured":"Niu, Y., Gu, L., Zhao, Y., Lu, F.: Explainable diabetic retinopathy detection and retinal image generation. IEEE J. Biomed. Health Inform. 26(1), 44\u201355 (2021)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"45_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2022.106648","volume":"216","author":"QT Pham","year":"2022","unstructured":"Pham, Q.T., Ahn, S., Shin, J., Song, S.J.: Generating future fundus images for early age-related macular degeneration based on generative adversarial networks. Comput. Methods Programs Biomed. 216, 106648 (2022)","journal-title":"Comput. Methods Programs Biomed."},{"issue":"3","key":"45_CR21","doi-asserted-by":"publisher","first-page":"25","DOI":"10.3390\/data3030025","volume":"3","author":"P Porwal","year":"2018","unstructured":"Porwal, P., et al.: Indian diabetic retinopathy image dataset (idrid): a database for diabetic retinopathy screening research. Data 3(3), 25 (2018)","journal-title":"Data"},{"key":"45_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.preteyeres.2018.07.004","volume":"67","author":"U Schmidt-Erfurth","year":"2018","unstructured":"Schmidt-Erfurth, U., Sadeghipour, A., Gerendas, B.S., Waldstein, S.M., Bogunovi\u0107, H.: Artificial intelligence in retina. Prog. Retin. Eye Res. 67, 1\u201329 (2018)","journal-title":"Prog. Retin. Eye Res."},{"key":"45_CR23","unstructured":"Shang, F., Fu, J., Yang, Y., Huang, H., Liu, J., Ma, L.: Synfundus: a synthetic fundus images dataset with millions of samples and multi-disease annotations (2023)"},{"key":"45_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103357","volume":"99","author":"J Silva-Rodriguez","year":"2025","unstructured":"Silva-Rodriguez, J., Chakor, H., Kobbi, R., Dolz, J., Ayed, I.B.: A foundation language-image model of the retina (flair): Encoding expert knowledge in text supervision. Med. Image Anal. 99, 103357 (2025)","journal-title":"Med. Image Anal."},{"key":"45_CR25","doi-asserted-by":"crossref","unstructured":"Sommer, A., et\u00a0al.: Challenges of ophthalmic care in the developing world. JAMA Ophthalmol. 132(5), 640\u2013644 (2014)","DOI":"10.1001\/jamaophthalmol.2014.84"},{"key":"45_CR26","unstructured":"Team, G., et\u00a0al.: Gemma 2: improving open language models at a practical size. arXiv preprint arXiv:2408.00118 (2024)"},{"key":"45_CR27","unstructured":"Yang, A., et\u00a0al.: Qwen2. 5 technical report. arXiv preprint arXiv:2412.15115 (2024)"},{"key":"45_CR28","unstructured":"Yang, Y., et al.: Mammodg: generalisable deep learning breaks the limits of cross-domain multi-center breast cancer screening. arXiv preprint arXiv:2308.01057 (2023)"},{"issue":"18","key":"45_CR29","doi-asserted-by":"publisher","first-page":"3603","DOI":"10.3390\/electronics13183603","volume":"13","author":"P Zhang","year":"2024","unstructured":"Zhang, P., et al.: Fundus image generation and classification of diabetic retinopathy based on convolutional neural network. Electronics 13(18), 3603 (2024)","journal-title":"Electronics"},{"issue":"1","key":"45_CR30","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/JBHI.2020.3045475","volume":"26","author":"Y Zhou","year":"2020","unstructured":"Zhou, Y., Wang, B., He, X., Cui, S., Shao, L.: Dr-gan: conditional generative adversarial network for fine-grained lesion synthesis on diabetic retinopathy images. IEEE J. Biomed. Health Inform. 26(1), 56\u201366 (2020)","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"7981","key":"45_CR31","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1038\/s41586-023-06555-x","volume":"622","author":"Y Zhou","year":"2023","unstructured":"Zhou, Y., et al.: A foundation model for generalizable disease detection from retinal images. Nature 622(7981), 156\u2013163 (2023)","journal-title":"Nature"},{"key":"45_CR32","unstructured":"Zhuo, L., et\u00a0al.: Lumina-next: making lumina-t2x stronger and faster with next-dit. arXiv preprint arXiv:2406.18583 (2024)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2025"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-05325-1_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T19:06:18Z","timestamp":1758308778000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-05325-1_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,20]]},"ISBN":["9783032053244","9783032053251"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-05325-1_45","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,9,20]]},"assertion":[{"value":"20 September 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Daejeon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Korea (Republic of)","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}