{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T20:32:19Z","timestamp":1772829139127,"version":"3.50.1"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031777851","type":"print"},{"value":"9783031777868","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\/978-3-031-77786-8_12","type":"book-chapter","created":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T13:23:48Z","timestamp":1737120228000},"page":"119-129","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Retinal IPA: Iterative KeyPoints Alignment for\u00a0Multimodal Retinal Imaging"],"prefix":"10.1007","author":[{"given":"Jiacheng","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dewei","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xing","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuankai K.","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ipek","family":"Oguz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,17]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","first-page":"5733","DOI":"10.1109\/TIP.2022.3201476","volume":"31","author":"C An","year":"2022","unstructured":"An, C., Wang, Y., Zhang, J., Nguyen, T.Q.: Self-supervised rigid registration for multimodal retinal images. IEEE Trans. Image Process. 31, 5733\u20135747 (2022)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"12_CR2","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","volume":"110","author":"H Bay","year":"2008","unstructured":"Bay, H., Ess, A., Tuytelaars, T., Van Gool, L.: Speeded-up robust features (SURF). Comput. Vis. Image Underst. 110(3), 346\u2013359 (2008)","journal-title":"Comput. Vis. Image Underst."},{"key":"12_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-3-031-19824-3_2","volume-title":"Computer Vision - ECCV 2022","author":"H Chen","year":"2022","unstructured":"Chen, H., et al.: ASpanFormer: detector-free image matching with adaptive span transformer. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13692, pp. 20\u201336. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19824-3_2"},{"key":"12_CR4","doi-asserted-by":"crossref","unstructured":"DeTone, D., Malisiewicz, T., Rabinovich, A.: SuperPoint: self-supervised interest point detection and description. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 224\u2013236 (2018)","DOI":"10.1109\/CVPRW.2018.00060"},{"key":"12_CR5","doi-asserted-by":"crossref","unstructured":"Edstedt, J., Athanasiadis, I., Wadenb\u00e4ck, M., Felsberg, M.: DKM: dense kernelized feature matching for geometry estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17765\u201317775 (2023)","DOI":"10.1109\/CVPR52729.2023.01704"},{"key":"12_CR6","doi-asserted-by":"crossref","unstructured":"Edstedt, J., Sun, Q., B\u00f6kman, G., Wadenb\u00e4ck, M., Felsberg, M.: RoMa: Revisiting robust losses for dense feature matching. arXiv preprint arXiv:2305.15404 (2023)","DOI":"10.1109\/CVPR52733.2024.01871"},{"issue":"6","key":"12_CR7","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1145\/358669.358692","volume":"24","author":"MA Fischler","year":"1981","unstructured":"Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381\u2013395 (1981)","journal-title":"Commun. ACM"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Gleize, P., Wang, W., Feiszli, M.: Silk\u2013simple learned keypoints. arXiv preprint arXiv:2304.06194 (2023)","DOI":"10.1109\/ICCV51070.2023.02056"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Hajeb Mohammad\u00a0Alipour, S., Rabbani, H., Akhlaghi, M.R.: Diabetic retinopathy grading by digital curvelet transform. Comput. Math. Methods Med. 2012 (2012)","DOI":"10.1155\/2012\/761901"},{"issue":"4","key":"12_CR10","doi-asserted-by":"publisher","first-page":"16","DOI":"10.35119\/maio.v1i4.42","volume":"1","author":"C Hernandez-Matas","year":"2017","unstructured":"Hernandez-Matas, C., Zabulis, X., Triantafyllou, A., Anyfanti, P., Douma, S., Argyros, A.A.: FIRE: fundus image registration dataset. Model. Artif. Intell. Ophthalmol. 1(4), 16\u201328 (2017)","journal-title":"Model. Artif. Intell. Ophthalmol."},{"key":"12_CR11","unstructured":"Kirillov, A., et\u00a0al.: Segment anything. arXiv preprint arXiv:2304.02643 (2023)"},{"key":"12_CR12","doi-asserted-by":"crossref","unstructured":"Lee, J.A., Liu, P., Cheng, J., Fu, H.: A deep step pattern representation for multimodal retinal image registration. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 5077\u20135086 (2019)","DOI":"10.1109\/ICCV.2019.00518"},{"key":"12_CR13","doi-asserted-by":"crossref","unstructured":"Li, H., et\u00a0al.: Self-supervised test-time adaptation for medical image segmentation. In: International Workshop on Machine Learning in Clinical Neuroimaging, pp. 32\u201341. Springer (2022)","DOI":"10.1007\/978-3-031-17899-3_4"},{"key":"12_CR14","doi-asserted-by":"crossref","unstructured":"Li, H., Liu, H., Hu, D., Wang, J., Oguz, I.: Promise: Prompt-driven 3D medical image segmentation using pretrained image foundation models. arXiv preprint arXiv:2310.19721 (2023)","DOI":"10.1109\/ISBI56570.2024.10635207"},{"key":"12_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103092","volume":"93","author":"M Li","year":"2024","unstructured":"Li, M., et al.: Octa-500: a retinal dataset for optical coherence tomography angiography study. Med. Image Anal. 93, 103092 (2024)","journal-title":"Med. Image Anal."},{"key":"12_CR16","doi-asserted-by":"crossref","unstructured":"Lindenberger, P., Sarlin, P.E., Pollefeys, M.: LightGlue: Local feature matching at light speed. arXiv preprint arXiv:2306.13643 (2023)","DOI":"10.1109\/ICCV51070.2023.01616"},{"key":"12_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"593","DOI":"10.1007\/978-3-031-19803-8_35","volume-title":"Computer Vision - ECCV 2022","author":"J Liu","year":"2022","unstructured":"Liu, J., Li, X., Wei, Q., Xu, J., Ding, D.: Semi-supervised keypoint detector and descriptor for retinal image matching. In: Avidan, S., Brostow, G., Ciss\u00e9, M., Farinella, G.M., Hassner, T. (eds.) ECCV 2022. LNCS, vol. 13681, pp. 593\u2013609. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-19803-8_35"},{"key":"12_CR18","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60, 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vision"},{"key":"12_CR19","unstructured":"Nasser, S.A., Gupte, N., Sethi, A.: Reverse knowledge distillation: Training a large model using a small one for retinal image matching on limited data (2023). https:\/\/www.dropbox.com\/sh\/o8q84e2eg54ay3d\/AADiAkNr6bFQDoFaKeEjpYtra?dl=0"},{"key":"12_CR20","unstructured":"Revaud, J., et al.: R2D2: repeatable and reliable detector and descriptor. arXiv preprint arXiv:1906.06195 (2019)"},{"key":"12_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015, Part III. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"388","key":"12_CR22","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1080\/01621459.1984.10477105","volume":"79","author":"PJ Rousseeuw","year":"1984","unstructured":"Rousseeuw, P.J.: Least median of squares regression. J. Am. Stat. Assoc. 79(388), 871\u2013880 (1984)","journal-title":"J. Am. Stat. Assoc."},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to sift or surf. In: 2011 International Conference on Computer Vision, pp. 2564\u20132571. IEEE (2011)","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"12_CR24","doi-asserted-by":"crossref","unstructured":"Sarlin, P.E., DeTone, D., Malisiewicz, T., Rabinovich, A.: SuperGlue: learning feature matching with graph neural networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4938\u20134947 (2020)","DOI":"10.1109\/CVPR42600.2020.00499"},{"key":"12_CR25","doi-asserted-by":"crossref","unstructured":"Sindel, A., Hohberger, B., Maier, A., Christlein, V.: Multi-modal retinal image registration using a keypoint-based vessel structure aligning network. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 108\u2013118. Springer (2022)","DOI":"10.1007\/978-3-031-16446-0_11"},{"key":"12_CR26","doi-asserted-by":"crossref","unstructured":"Sun, J., Shen, Z., Wang, Y., Bao, H., Zhou, X.: LoFTR: detector-free local feature matching with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 8922\u20138931 (2021)","DOI":"10.1109\/CVPR46437.2021.00881"},{"key":"12_CR27","doi-asserted-by":"crossref","unstructured":"Truong, P., Apostolopoulos, S., Mosinska, A., Stucky, S., Ciller, C., Zanet, S.D.: GLAMpoints: greedily learned accurate match points. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10732\u201310741 (2019)","DOI":"10.1109\/ICCV.2019.01083"},{"key":"12_CR28","first-page":"14254","volume":"33","author":"M Tyszkiewicz","year":"2020","unstructured":"Tyszkiewicz, M., Fua, P., Trulls, E.: DISK: learning local features with policy gradient. Adv. Neural. Inf. Process. Syst. 33, 14254\u201314265 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"12_CR29","doi-asserted-by":"publisher","first-page":"68","DOI":"10.1016\/j.bspc.2015.03.004","volume":"19","author":"G Wang","year":"2015","unstructured":"Wang, G., Wang, Z., Chen, Y., Zhao, W.: Robust point matching method for multimodal retinal image registration. Biomed. Signal Process. Control 19, 68\u201376 (2015)","journal-title":"Biomed. Signal Process. Control"},{"key":"12_CR30","doi-asserted-by":"crossref","unstructured":"Wang, J., Li, H., Hu, D., Tao, Y.K., Oguz, I.: Novel oct mosaicking pipeline with feature-and pixel-based registration. arXiv preprint arXiv:2311.13052 (2023)","DOI":"10.1109\/ISBI56570.2024.10635432"},{"key":"12_CR31","unstructured":"Yang, Z., Ren, M., Ding, K., Gerig, G., Wang, Y.: Keypoint-augmented self-supervised learning for medical image segmentation with limited annotation. Adv. Neural Inf. Process. Syst. 36 (2024)"},{"key":"12_CR32","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/978-3-030-87196-3_21","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"D Zeng","year":"2021","unstructured":"Zeng, D., et al.: Positional contrastive learning for\u00a0volumetric medical image segmentation. In: de Bruijne, M., et al. (eds.) MICCAI 2021, Part II. LNCS, vol. 12902, pp. 221\u2013230. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87196-3_21"}],"container-title":["Lecture Notes in Computer Science","Medical Optical Imaging and Virtual Microscopy Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-77786-8_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T13:24:00Z","timestamp":1737120240000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-77786-8_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031777851","9783031777868"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-77786-8_12","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":"17 January 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":"MOVI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Medical Optical Imaging and Virtual Microscopy Image Analysis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","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":"10 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"movi2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/movi2024","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}