{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T08:09:22Z","timestamp":1783930162731,"version":"3.55.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819235032","type":"print"},{"value":"9789819235049","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"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\/978-981-92-3504-9_28","type":"book-chapter","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:34:52Z","timestamp":1783928092000},"page":"341-351","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["EPRV-SAM: Efficient Self-Prompted Retinal Vessel Segmentation Based on SAM"],"prefix":"10.1007","author":[{"given":"Wei","family":"Guo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiran","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhaoxuan","family":"Gong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guodong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,14]]},"reference":[{"key":"28_CR1","doi-asserted-by":"publisher","first-page":"1292","DOI":"10.1007\/s10439-022-03058-0","volume":"50","author":"A Khandouzi","year":"2022","unstructured":"Khandouzi, A., et al.: Retinal vessel segmentation, a review of classic and deep methods. Ann. Biomed. Eng. 50, 1292\u20131314 (2022)","journal-title":"Ann. Biomed. Eng."},{"key":"28_CR2","doi-asserted-by":"publisher","DOI":"10.1002\/ima.22945","volume":"34","author":"K Radha","year":"2024","unstructured":"Radha, K., et al.: Retinal vessel segmentation to diagnose diabetic retinopathy using fundus images: a survey. Int. J. Imaging Syst. Technol. 34, e22945 (2024)","journal-title":"Int. J. Imaging Syst. Technol."},{"key":"28_CR3","first-page":"234","volume-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., et al.: U-net: convolutional networks for biomedical image segmentation. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 234\u2013241. Springer (2015)"},{"key":"28_CR4","first-page":"11480","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"J-H Nam","year":"2024","unstructured":"Nam, J.-H., et al.: Modality-agnostic domain generalizable medical image segmentation by multi-frequency in multi-scale attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11480\u201311491 (2024)"},{"key":"28_CR5","first-page":"4015","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"A Kirillov","year":"2023","unstructured":"Kirillov, A., et al.: Segment anything. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 4015\u20134026 (2023)"},{"key":"28_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.108238","volume":"171","author":"Y Zhang","year":"2024","unstructured":"Zhang, Y., et al.: Segment anything model for medical image segmentation: current applications and future directions. Comput. Biol. Med. 171, 108238 (2024)","journal-title":"Comput. Biol. Med."},{"key":"28_CR7","doi-asserted-by":"publisher","first-page":"7406","DOI":"10.1007\/s11263-025-02539-8","volume":"133","author":"X Sun","year":"2025","unstructured":"Sun, X., et al.: On efficient variants of segment anything model: a survey. Int. J. Comput. Vis. 133, 7406\u20137436 (2025)","journal-title":"Int. J. Comput. Vis."},{"key":"28_CR8","doi-asserted-by":"publisher","DOI":"10.3390\/app12136393","volume":"12","author":"N Muzammil","year":"2022","unstructured":"Muzammil, N., et al.: Multifilters-based unsupervised method for retinal blood vessel segmentation. Appl. Sci. 12, 6393 (2022)","journal-title":"Appl. Sci."},{"key":"28_CR9","doi-asserted-by":"crossref","unstructured":"Zhou, Z. et al.: Unet++: redesigning skip connections to exploit multiscale features in image segmentation. IEEE Trans. Med. Imaging 39, 1856\u20131867 (2019).","DOI":"10.1109\/TMI.2019.2959609"},{"key":"28_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109512","volume":"253","author":"Z Han","year":"2022","unstructured":"Han, Z., et al.: ConvUNeXt: an efficient convolution neural network for medical image segmentation. Knowl.-Based Syst. 253, 109512 (2022)","journal-title":"Knowl.-Based Syst."},{"key":"28_CR11","doi-asserted-by":"publisher","first-page":"4623","DOI":"10.1109\/JBHI.2022.3188710","volume":"26","author":"W Liu","year":"2022","unstructured":"Liu, W., et al.: Full-resolution network and dual-threshold iteration for retinal vessel and coronary angiograph segmentation. IEEE J. Biomed. Health Inform. 26, 4623\u20134634 (2022)","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"28_CR12","doi-asserted-by":"publisher","first-page":"654","DOI":"10.1038\/s41467-024-44824-z","volume":"15","author":"J Ma","year":"2024","unstructured":"Ma, J., et al.: Segment anything in medical images. Nat. Commun. 15, 654 (2024)","journal-title":"Nat. Commun."},{"key":"28_CR13","first-page":"3367","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"T Chen","year":"2023","unstructured":"Chen, T., et al.: Sam-adapter: adapting segment anything in underperformed scenes. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3367\u20133375 (2023)"},{"key":"28_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2025.103547","volume":"102","author":"J Wu","year":"2025","unstructured":"Wu, J., et al.: Medical SAM adapter: adapting segment anything model for medical image segmentation. Med. Image Anal. 102, 103547 (2025)","journal-title":"Med. Image Anal."},{"key":"28_CR15","first-page":"3","volume-title":"ICLR","author":"EJ Hu","year":"2022","unstructured":"Hu, E.J., et al.: LoRA: low-rank adaptation of large language models. In: ICLR, vol. 1, p. 3 (2022)"},{"key":"28_CR16","unstructured":"Qiu, Z., et al.: Learnable ophthalmology SAM. arXiv preprint arXiv:2304.13425. (2023)"},{"key":"28_CR17","volume-title":"De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation","author":"Q Xu","year":"2025","unstructured":"Xu, Q. et al.: De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation (2025)."},{"key":"28_CR18","unstructured":"Zhang, C., et al.: Faster segment anything: towards lightweight SAM for mobile applications. arXiv preprint arXiv:2306.14289. (2023)"},{"key":"28_CR19","first-page":"3210","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"Z Chen","year":"2026","unstructured":"Chen, Z., et al.: CaPro: curvilinear-aware prompt learning with single unlabeled image for cost-effective curvilinear structure segmentation. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp. 3210\u20133218 (2026)"},{"key":"28_CR20","first-page":"4510","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"M Sandler","year":"2018","unstructured":"Sandler, M., et al.: MobileNetV2: inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018)"},{"key":"28_CR21","first-page":"7132","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"J Hu","year":"2018","unstructured":"Hu, J., et al.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)"},{"key":"28_CR22","doi-asserted-by":"publisher","first-page":"2538","DOI":"10.1109\/TBME.2012.2205687","volume":"59","author":"MM Fraz","year":"2012","unstructured":"Fraz, M.M., et al.: An ensemble classification-based approach applied to retinal blood vessel segmentation. IEEE Trans. Biomed. Eng. 59, 2538\u20132548 (2012)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"28_CR23","doi-asserted-by":"crossref","unstructured":"Hoover, A. et al.: Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response. IEEE Trans. Med. Imaging 19, 203\u2013210 (2000)","DOI":"10.1109\/42.845178"},{"key":"28_CR24","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/TMI.2004.825627","volume":"23","author":"J Staal","year":"2004","unstructured":"Staal, J., et al.: Ridge-based vessel segmentation in color images of the retina. IEEE Trans. Med. Imaging. 23, 501\u2013509 (2004)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"28_CR25","first-page":"6023","volume-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","author":"S Yun","year":"2019","unstructured":"Yun, S., et al.: CutMix: regularization strategy to train strong classifiers with localizable features. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6023\u20136032 (2019)"}],"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\/978-981-92-3504-9_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T07:34:55Z","timestamp":1783928095000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-92-3504-9_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"ISBN":["9789819235032","9789819235049"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-92-3504-9_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,14]]},"assertion":[{"value":"14 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"}}]}}