{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T01:15:03Z","timestamp":1770340503900,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":25,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819756889","type":"print"},{"value":"9789819756896","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-981-97-5689-6_34","type":"book-chapter","created":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:02:35Z","timestamp":1722326555000},"page":"393-404","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["FD-SDG: Frequency Dropout Based Single Source Domain Generalization Framework for Retinal Vessel Segmentation"],"prefix":"10.1007","author":[{"given":"Boyang","family":"Li","sequence":"first","affiliation":[]},{"given":"Haojin","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yule","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Heng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jiangyu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Fuhai","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Jianwen","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Jiang","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"34_CR1","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1109\/TMI.2022.3210133","volume":"42","author":"S Hu","year":"2021","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, 233\u2013244 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"34_CR2","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 (2023)","DOI":"10.1109\/ISBI53787.2023.10230561"},{"key":"34_CR3","unstructured":"Li, H., et al.: RaffeSDG: Random Frequency Filtering enabled Single-source Domain Generalization for Medical Image Segmentation (2024)"},{"key":"34_CR4","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1109\/TMI.2022.3224067","volume":"42","author":"C Ouyang","year":"2021","unstructured":"Ouyang, C., et al.: Causality-inspired single-source domain generalization for medical image segmentation. IEEE Trans. Med. Imaging 42, 1095\u20131106 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"34_CR5","doi-asserted-by":"crossref","unstructured":"Su, Z., Yao, K., Yang, X., Wang, Q., Sun, J., Huang, K.: Rethinking data augmentation for single-source domain generalization in medical image segmentation. In: AAAI Conference on Artificial Intelligence (2022)","DOI":"10.1609\/aaai.v37i2.25332"},{"key":"34_CR6","doi-asserted-by":"publisher","first-page":"102945","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":"34_CR7","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. Imaging 43, 1323\u20131336 (2023)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"34_CR8","doi-asserted-by":"crossref","unstructured":"Li, H., et al.: Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation. ArXiv, abs\/2307.09005 (2023)","DOI":"10.1007\/978-3-031-43987-2_13"},{"key":"34_CR9","first-page":"14378","volume":"2021","author":"Q Xu","year":"2021","unstructured":"Xu, Q., Zhang, R., Zhang, Y., Wang, Y., Tian, Q.: A fourier-based framework for domain generalization. IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR) 2021, 14378\u201314387 (2021)","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR)"},{"key":"34_CR10","first-page":"4164","volume":"2022","author":"I \u00c7ugu","year":"2022","unstructured":"\u00c7ugu, I., Mancini, M., Chen, Y., Akata, Z.: Attention consistency on visual corruptions for single-source domain generalization. IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. Workshops (CVPRW) 2022, 4164\u20134173 (2022)","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. Workshops (CVPRW)"},{"key":"34_CR11","doi-asserted-by":"crossref","unstructured":"Li, H., Li, H., Qiu, Z., Hu, Y., Liu, J.: Domain Adaptive Retinal Vessel Segmentation Guided by High-frequency Component. OMIA@MICCAI (2022)","DOI":"10.1007\/978-3-031-16525-2_12"},{"key":"34_CR12","unstructured":"Hinton, G.E., Srivastava, N., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.. Improving neural networks by preventing co-adaptation of feature detectors. ArXiv, abs\/1207.0580 (2012)"},{"key":"34_CR13","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 (2022)","DOI":"10.1109\/EMBC48229.2022.9871673"},{"key":"34_CR14","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G.E., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929\u20131958 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"34_CR15","unstructured":"Inoue, H.: Multi-Sample Dropout for Accelerated Training and Better Generalization. ArXiv, abs\/1905.09788 (2019)"},{"key":"34_CR16","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.inffus.2019.10.003","volume":"56","author":"AV Vanmali","year":"2020","unstructured":"Vanmali, A.V., Kataria, T., Kelkar, S.G., Gadre, V.M.: Ringing artifacts in wavelet based image fusion: analysis, measurement and remedies. Inf. Fusion 56, 39\u201369 (2020)","journal-title":"Inf. Fusion"},{"key":"34_CR17","first-page":"14197","volume":"2022","author":"L Zhao","year":"2022","unstructured":"Zhao, L., Wang, L.: Task-specific inconsistency alignment for domain adaptive object detection. IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR) 2022, 14197\u201314206 (2022)","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR)"},{"key":"34_CR18","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J., Kweon, I.: CBAM: Convolutional Block Attention Module. ArXiv, abs\/1807.06521 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"34_CR19","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/TMI.2004.825627","volume":"23","author":"J Staal","year":"2004","unstructured":"Staal, J., Abr\u00e0moff, M.D., Niemeijer, M., Viergever, M.A., Ginneken, B.V.: Ridge-based vessel segmentation in color images of the retina. IEEE Trans. Med. Imaging 23, 501\u2013509 (2004)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"22","key":"34_CR20","doi-asserted-by":"publisher","first-page":"2402","DOI":"10.1001\/jama.2016.17216","volume":"316","author":"V Gulshan","year":"2016","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)","journal-title":"JAMA"},{"key":"34_CR21","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.J., Pluim, J.P., Duits, R., Romeny, B.M.: Robust retinal vessel segmentation via locally adaptive derivative frames in orientation scores. IEEE Trans. Med. Imaging 35, 2631\u20132644 (2016)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"34_CR22","doi-asserted-by":"crossref","unstructured":"Orlando, J.I., Breda, J.B., Keer, K.V., Blaschko, M.B., Blanco, P.J., Bulant, C.A. Towards a glaucoma risk index based on simulated hemodynamics from fundus images. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (2018)","DOI":"10.1007\/978-3-030-00934-2_8"},{"key":"34_CR23","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 multi-ethnic population study of 10-year-old children; the child heart and health study in England (CHASE). Arterioscler. Thromb. Vasc. Biol. 31, 1933\u20131938 (2011)","journal-title":"Arterioscler. Thromb. Vasc. Biol."},{"key":"34_CR24","first-page":"2584","volume":"2022","author":"D Peng","year":"2022","unstructured":"Peng, D., Lei, Y., Hayat, M., Guo, Y., Li, W.: Semantic-aware domain generalized segmentation. IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR) 2022, 2584\u20132595 (2022)","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR)"},{"key":"34_CR25","first-page":"1013","volume":"2021","author":"Q Liu","year":"2021","unstructured":"Liu, Q., Chen, C., Qin, J., Dou, Q., Heng, P.: FedDG: federated domain generalization on medical image segmentation via episodic learning in continuous frequency space. IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR) 2021, 1013\u20131023 (2021)","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recogn. (CVPR)"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5689-6_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,30]],"date-time":"2024-07-30T08:07:53Z","timestamp":1722326873000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5689-6_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756889","9789819756896"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5689-6_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"31 July 2024","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":"Tianjin","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":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}