{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T04:05:58Z","timestamp":1779422758495,"version":"3.53.1"},"publisher-location":"Singapore","reference-count":29,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819500352","type":"print"},{"value":"9789819500369","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-981-95-0036-9_23","type":"book-chapter","created":{"date-parts":[[2025,7,23]],"date-time":"2025-07-23T08:37:38Z","timestamp":1753259858000},"page":"270-281","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["BIRF-SDG: Band Importance Aware Random Frequency Filter Based Single-Source Domain Generalization for Retinal Vessel Segmentation"],"prefix":"10.1007","author":[{"given":"Bingqin","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haojin","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heng","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hemu","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,7,24]]},"reference":[{"key":"23_CR1","doi-asserted-by":"crossref","unstructured":"Cugu, I., Mancini, M., Chen, Y., Akata, Z.: Attention consistency on visual corruptions for single-source domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4165\u20134174 (2022)","DOI":"10.1109\/CVPRW56347.2022.00461"},{"issue":"5","key":"23_CR2","doi-asserted-by":"publisher","first-page":"3057","DOI":"10.1103\/PhysRevD.56.3057","volume":"56","author":"A Dobado","year":"1997","unstructured":"Dobado, A., Pelaez, J.: Inverse amplitude method in chiral perturbation theory. Phys. Rev. D 56(5), 3057 (1997)","journal-title":"Phys. Rev. D"},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Gulshan, V., et al.: 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"},{"key":"23_CR4","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.R.: Improving neural networks by preventing co-adaptation of feature detectors. arXiv preprint arXiv:1207.0580 (2012)"},{"issue":"1","key":"23_CR5","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1109\/TMI.2022.3210133","volume":"42","author":"S Hu","year":"2022","unstructured":"Hu, S., Liao, Z., Zhang, J., Xia, Y.: Domain and content adaptive convolution based multi-source domain generalization for medical image segmentation. IEEE Trans. Med. Imaging 42(1), 233\u2013244 (2022)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"23_CR6","unstructured":"Inoue, H.: Multi-sample dropout for accelerated training and better generalization. arXiv preprint arXiv:1905.09788 (2019)"},{"key":"23_CR7","doi-asserted-by":"publisher","unstructured":"Li, B., et al.: FD-SDG: frequency dropout based single source domain generalization framework for retinal vessel segmentation. In: Huang, DS., Zhang, Q., Guo, J. (eds.) International Conference on Intelligent Computing. pp. 393\u2013404. Springer, Singapore (2024). https:\/\/doi.org\/10.1007\/978-981-97-5689-6_34","DOI":"10.1007\/978-981-97-5689-6_34"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Li, H., et al.: AIF-SFDA: autonomous information filter-driven source-free domain adaptation for medical image segmentation. arXiv preprint arXiv:2501.03074 (2025)","DOI":"10.1609\/aaai.v39i5.32498"},{"key":"23_CR9","doi-asserted-by":"publisher","unstructured":"Li, H., Li, H., Qiu, Z., Hu, Y., Liu, J.: Domain adaptive retinal vessel segmentation guided by high-frequency component. In: Antony, B., Fu, H., Lee, C.S., MacGillivray, T., Xu, Y., Zheng, Y. (eds.) International Workshop on Ophthalmic Medical Image Analysis, pp. 115\u2013124. Springer (2022). https:\/\/doi.org\/10.1007\/978-3-031-16525-2_12","DOI":"10.1007\/978-3-031-16525-2_12"},{"key":"23_CR10","doi-asserted-by":"crossref","unstructured":"Li, H., Li, H., Shu, H., Chen, J., Hu, Y., Liu, J.: Self-supervision boosted retinal vessel segmentation for cross-domain data. In: 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI). pp. 1\u20135. IEEE (2023)","DOI":"10.1109\/ISBI53787.2023.10230561"},{"key":"23_CR11","unstructured":"Li, H., et al.: RaffeSDG: random frequency filtering enabled single-source domain generalization for medical image segmentation. arXiv preprint arXiv:2405.01228 (2024)"},{"key":"23_CR12","doi-asserted-by":"publisher","unstructured":"Li, H., et al.: Frequency-mixed single-source domain generalization for medical image segmentation. In: Greenspan, H., et al. (eds.) International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 127\u2013136. Springer (2023). https:\/\/doi.org\/10.1007\/978-3-031-43987-2_13","DOI":"10.1007\/978-3-031-43987-2_13"},{"issue":"4","key":"23_CR13","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1109\/TMI.2023.3335651","volume":"43","author":"H Li","year":"2023","unstructured":"Li, H., et al.: Enhancing and adapting in the clinic: source-free unsupervised domain adaptation for medical image enhancement. IEEE Trans. Med. Imag. 43(4), 1323\u20131336 (2023)","journal-title":"IEEE Trans. Med. Imag."},{"key":"23_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102945","volume":"90","author":"H Li","year":"2023","unstructured":"Li, H., et al.: A generic fundus image enhancement network boosted by frequency self-supervised representation learning. Med. Image Anal. 90, 102945 (2023)","journal-title":"Med. Image Anal."},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Liu, Q., Chen, C., Qin, J., Dou, Q., Heng, P.A.: FedDG: federated domain generalization on medical image segmentation via episodic learning in continuous frequency space. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1013\u20131023 (2021)","DOI":"10.1109\/CVPR46437.2021.00107"},{"key":"23_CR16","first-page":"1","volume":"15","author":"S Nitish","year":"2014","unstructured":"Nitish, S.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"23_CR17","doi-asserted-by":"publisher","unstructured":"Orlando, J.I., Barbosa Breda, J., Van Keer, K., Blaschko, M.B., Blanco, P.J., Bulant, C.A.: Towards a glaucoma risk index based on simulated hemodynamics from fundus images. In: Frangi, A., Schnabel, J., Davatzikos, C., Alberola-L\u00f3pez, C., Fichtinger, G. (eds.) Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2018: 21st International Conference, Granada, Spain, September 16\u201320, 2018, Proceedings, Part II 11, pp. 65\u201373. Springer (2018). https:\/\/doi.org\/10.1007\/978-3-030-00934-2_8","DOI":"10.1007\/978-3-030-00934-2_8"},{"key":"23_CR18","doi-asserted-by":"crossref","unstructured":"Ou, M., et al.: MVD-Net: semantic segmentation of cataract surgery using multi-view learning. In: 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), pp. 5035\u20135038. IEEE (2022)","DOI":"10.1109\/EMBC48229.2022.9871673"},{"issue":"4","key":"23_CR19","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1109\/TMI.2022.3224067","volume":"42","author":"C Ouyang","year":"2022","unstructured":"Ouyang, C., et al.: Causality-inspired singlesource domain generalization for medical image segmentation. IEEE Trans. Med. Imaging 42(4), 1095\u20131106 (2022)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"8","key":"23_CR20","doi-asserted-by":"publisher","first-page":"1933","DOI":"10.1161\/ATVBAHA.111.225219","volume":"31","author":"CG Owen","year":"2011","unstructured":"Owen, C.G., et al.: Retinal arteriolar tortuosity and cardiovascular risk factors in a multiethnic population study of 10-year-old children; the child heart and health study in England (chase). Arterioscler. Thromb. Vasc. Biol. 31(8), 1933\u20131938 (2011)","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"23_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2024.102800","volume":"150","author":"X Shu","year":"2024","unstructured":"Shu, X., Wang, J., Zhang, A., Shi, J., Wu, X.J.: CSCA U-Net: a channel and space compound attention CNN for medical image segmentation. Artif. Intell. Med. 150, 102800 (2024)","journal-title":"Artif. Intell. Med."},{"key":"23_CR22","doi-asserted-by":"crossref","unstructured":"Staal, J., Abr`amoff, M.D., Niemeijer, M., Viergever, M.A., Van Ginneken, B.: Ridge-based vessel segmentation in color images of the retina. IEEE Trans. Med. Imag. 23(4), 501\u2013509 (2004)","DOI":"10.1109\/TMI.2004.825627"},{"key":"23_CR23","doi-asserted-by":"crossref","unstructured":"Su, Z., Yao, K., Yang, X., Huang, K., Wang, Q., Sun, J.: Rethinking data augmentation for single-source domain generalization in medical image segmentation. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, pp. 2366\u20132374 (2023) 4","DOI":"10.1609\/aaai.v37i2.25332"},{"key":"23_CR24","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., Kweon, I.S.: CBAM: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"23_CR25","doi-asserted-by":"crossref","unstructured":"Xu, Q., Zhang, R., Zhang, Y., Wang, Y., Tian, Q.: A fourier-based framework for domain generalization. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14383\u201314392 (2021)","DOI":"10.1109\/CVPR46437.2021.01415"},{"issue":"12","key":"23_CR26","doi-asserted-by":"publisher","first-page":"2631","DOI":"10.1109\/TMI.2016.2587062","volume":"35","author":"J Zhang","year":"2016","unstructured":"Zhang, J., Dashtbozorg, B., Bekkers, E., Pluim, J.P., Duits, R., ter Haar Romeny, B.M.: Robust retinal vessel segmentation via locally adaptive derivative frames in orientation scores. IEEE Trans. Med. Imaging 35(12), 2631\u20132644 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"23_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109667","volume":"141","author":"W Zhang","year":"2023","unstructured":"Zhang, W., Ding, X., Liu, Y., Qiao, B.: Slide deep reinforcement learning networks: application for left ventricle segmentation. Pattern Recogn. 141, 109667 (2023)","journal-title":"Pattern Recogn."},{"key":"23_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.106638","volume":"96","author":"W Zhang","year":"2024","unstructured":"Zhang, W., Li, S., Wang, Y., Zhang, W.: EEMSNet: eagle-eye multi-scale supervised network for cardiac segmentation. Biomed. Signal Process. Control 96, 106638 (2024)","journal-title":"Biomed. Signal Process. Control"},{"key":"23_CR29","doi-asserted-by":"crossref","unstructured":"Zhao, L., Wang, L.: Task-specific inconsistency alignment for domain adaptive object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 14217\u201314226 (2022)","DOI":"10.1109\/CVPR52688.2022.01382"}],"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\/978-981-95-0036-9_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T03:12:10Z","timestamp":1779419530000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-0036-9_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819500352","9789819500369"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-0036-9_23","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"24 July 2025","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":"Ningbo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","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":"26 July 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 July 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/icg\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}