{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:04:11Z","timestamp":1784405051466,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819235001","type":"print"},{"value":"9789819235018","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,19]],"date-time":"2026-07-19T00:00:00Z","timestamp":1784419200000},"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":[[2027]]},"DOI":"10.1007\/978-981-92-3501-8_25","type":"book-chapter","created":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:00:45Z","timestamp":1784404845000},"page":"296-307","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Improved Conditional Diffusion Framework for Retinal Vessel Image Generation"],"prefix":"10.1007","author":[{"given":"Xiaokang","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,19]]},"reference":[{"key":"25_CR1","first-page":"1","volume-title":"2023 IEEE International Conference on Computational Photography (ICCP)","author":"A Alimanov","year":"2023","unstructured":"Alimanov, A., Islam, M.B.: Denoising diffusion probabilistic model for retinal image generation and segmentation. In: 2023 IEEE International Conference on Computational Photography (ICCP), pp. 1\u201312. IEEE (2023)"},{"issue":"3","key":"25_CR2","doi-asserted-by":"publisher","first-page":"781","DOI":"10.1109\/TMI.2017.2759102","volume":"37","author":"P Costa","year":"2017","unstructured":"Costa, P. et al.: End-to-end adversarial retinal image synthesis. IEEE Trans. Med. Imaging. 37(3), 781\u2013791 (2017)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"25_CR3","first-page":"8780","volume":"34","author":"P Dhariwal","year":"2021","unstructured":"Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. Adv. Neural Inform. Process. Syst. 34, 8780\u20138794 (2021)","journal-title":"Adv. Neural Inform. Process. Syst."},{"key":"25_CR4","first-page":"1","volume-title":"2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","author":"Z Dorjsembe","year":"2024","unstructured":"Dorjsembe, Z., Pao, H.K., Xiao, F.: Polyp-DDPM: diffusion-based semantic polyp synthesis for enhanced segmentation. In: 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1\u20137. IEEE (2024)"},{"key":"25_CR5","unstructured":"Fhima, J. et al.: Enhancing retinal vessel segmentation generalization via layout-aware generative modelling. arXiv Preprint. https:\/\/arxiv.org\/abs\/2503.01190 (2025)"},{"key":"25_CR6","first-page":"48","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"H Fu","year":"2019","unstructured":"Fu, H. et al.: Evaluation of retinal image quality assessment networks in different color-spaces. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 48\u201356. Springer (2019)"},{"key":"25_CR7","first-page":"2335","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"S Go","year":"2024","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)"},{"key":"25_CR8","volume-title":"Advances in Neural Information Processing Systems","author":"IJ Goodfellow","year":"2014","unstructured":"Goodfellow, I.J. et al.: Generative Adversarial Nets. In: Advances in Neural Information Processing Systems, vol. 27,  (2014)"},{"key":"25_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2022.104004","volume":"78","author":"X Guo","year":"2022","unstructured":"Guo, X., Lu, X., Lin, Q., Zhang, J., Hu, X., Che, S.: A novel retinal image generation model with the preservation of structural similarity and high resolution. Biomed. Signal Process. Control. 78, 104004 (2022)","journal-title":"Biomed. Signal Process. Control"},{"key":"25_CR10","first-page":"6840","volume-title":"Advances in Neural Information Processing Systems","author":"J Ho","year":"2020","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising diffusion probabilistic models. In: Advances in Neural Information Processing Systems, vol. 33, pp. 6840\u20136851 (2020)"},{"issue":"1","key":"25_CR11","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":"4","key":"25_CR12","doi-asserted-by":"publisher","first-page":"730","DOI":"10.1007\/s11633-025-1562-4","volume":"22","author":"C Lu","year":"2025","unstructured":"Lu, C., Zhou, Y., Bao, F., Chen, J., Li, C., Zhu, J.: DPM-solver++: fast solver for guided sampling of diffusion probabilistic models. Mach. Intell. Res. 22(4), 730\u2013751 (2025)","journal-title":"Mach. Intell. Res."},{"key":"25_CR13","first-page":"8162","volume-title":"International Conference on Machine Learning","author":"AQ Nichol","year":"2021","unstructured":"Nichol, A.Q., Dhariwal, P.: Improved denoising diffusion probabilistic models. In: International Conference on Machine Learning, pp. 8162\u20138171. PMLR (2021)"},{"issue":"7","key":"25_CR14","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1136\/bjo-2024-326122","volume":"109","author":"PU Pandey","year":"2025","unstructured":"Pandey, P.U., Micieli, J.A., Ong Tone, S., Eng, K.T., Kertes, P.J., Wong, J.C.: Realistic fundus photograph generation for improving automated disease classification. Br. J. Ophthalmol. 109(7), 791\u2013798 (2025)","journal-title":"Br. J. Ophthalmol."},{"key":"25_CR15","first-page":"4195","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"W Peebles","year":"2023","unstructured":"Peebles, W., Xie, S.: Scalable diffusion models with transformers. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4195\u20134205. IEEE (2023)"},{"issue":"1","key":"25_CR16","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1186\/s12880-025-01694-1","volume":"25","author":"K Radha","year":"2025","unstructured":"Radha, K., Karuna, Y.: Latent space autoencoder generative adversarial model for retinal image synthesis and vessel segmentation. BMC Med. Imaging. 25(1), 149 (2025)","journal-title":"BMC Med. Imaging"},{"key":"25_CR17","first-page":"10684","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"R Rombach","year":"2022","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 10684\u201310695 (2022)"},{"issue":"2","key":"25_CR18","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10462-023-10624-y","volume":"57","author":"MM Saad","year":"2024","unstructured":"Saad, M.M., O\u2019Reilly, R., Rehmani, M.H.: A survey on training challenges in generative adversarial networks for biomedical image analysis. Artif. Intell. Rev. 57(2), 19 (2024)","journal-title":"Artif. Intell. Rev."},{"key":"25_CR19","unstructured":"Salimans, T., Ho, J.: Progressive distillation for fast sampling of diffusion models. arXiv Preprint. https:\/\/arxiv.org\/abs\/2202.00512 (2022)"},{"key":"25_CR20","unstructured":"Song, J., Meng, C., Ermon, S.: Denoising diffusion implicit models. arXiv Preprint. https:\/\/arxiv.org\/abs\/2010.02502 (2020)"},{"key":"25_CR21","volume-title":"Proceedings of the European Conference on Computer Vision (ECCV) Workshops","author":"X Wang","year":"2018","unstructured":"Wang, X. et al.: ESRGAN: enhanced super-resolution generative adversarial networks. In: Proceedings of the European Conference on Computer Vision (ECCV) Workshops (2018)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-92-3501-8_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,18]],"date-time":"2026-07-18T20:00:48Z","timestamp":1784404848000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3501-8_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,19]]},"ISBN":["9789819235001","9789819235018"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3501-8_25","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,19]]},"assertion":[{"value":"19 July 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Toronto","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2026","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 July 2026","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 July 2026","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2026a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2026\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}