{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T19:50:24Z","timestamp":1779306624772,"version":"3.51.4"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T00:00:00Z","timestamp":1739404800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T00:00:00Z","timestamp":1739404800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Northwest University 2024 Graduate Research and Innovation Program","award":["CX2024202"],"award-info":[{"award-number":["CX2024202"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62271393"],"award-info":[{"award-number":["62271393"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Technology Innovation Leading Project of Shaanxi","award":["2024QY-SZX-11"],"award-info":[{"award-number":["2024QY-SZX-11"]}]},{"name":"Xi\u2019an Science and Technology Programme Demonstration Project on Science and Technology Innovation for Social Development","award":["24SFSF0002"],"award-info":[{"award-number":["24SFSF0002"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s00530-025-01699-4","type":"journal-article","created":{"date-parts":[[2025,2,13]],"date-time":"2025-02-13T12:54:39Z","timestamp":1739451279000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["IOPCNet: inner and outer point classification based low overlap rate local-to-global point cloud registration"],"prefix":"10.1007","volume":"31","author":[{"given":"Jian","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuhe","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinghao","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tong","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengbo","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wuyang","family":"Shui","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guohua","family":"Geng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,13]]},"reference":[{"key":"1699_CR1","unstructured":"Huang, X., Mei, G., Zhang, J., Abbas, R.: A comprehensive survey on point cloud registration. arXiv preprint arXiv:2103.02690 (2021)"},{"key":"1699_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107691","volume":"111","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Li, C., Guo, B., Guo, C., Zhang, S.: Kdd: A kernel density based descriptor for 3d point clouds. Pattern Recogn. 111, 107691 (2021). https:\/\/doi.org\/10.1016\/j.patcog.2020.107691","journal-title":"Pattern Recogn."},{"key":"1699_CR3","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.isprsjprs.2023.01.013","volume":"197","author":"X Wang","year":"2023","unstructured":"Wang, X., Yang, Z., Cheng, X., Stoter, J., Xu, W., Wu, Z., Nan, L.: Globalmatch: Registration of forest terrestrial point clouds by global matching of relative stem positions. ISPRS J. Photogram. Remote Sens. 197, 71\u201386 (2023). https:\/\/doi.org\/10.1016\/j.isprsjprs.2023.01.013","journal-title":"ISPRS J. Photogram. Remote Sens."},{"issue":"2","key":"1699_CR4","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14(2), 239\u2013256 (1992). https:\/\/doi.org\/10.1109\/34.121791","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1699_CR5","doi-asserted-by":"publisher","unstructured":"Rusu, R.B., Blodow, N., Beetz, M.: Fast point feature histograms (fpfh) for 3d registration. In: 2009 IEEE International Conference on Robotics and Automation, pp. 3212\u20133217 (2009). https:\/\/doi.org\/10.1109\/ROBOT.2009.5152473","DOI":"10.1109\/ROBOT.2009.5152473"},{"key":"1699_CR6","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1016\/j.cviu.2014.04.011","volume":"125","author":"S Salti","year":"2014","unstructured":"Salti, S., Tombari, F., Di Stefano, L.: Shot: Unique signatures of histograms for surface and texture description. Comput. Vis. Image Underst. 125, 251\u2013264 (2014). https:\/\/doi.org\/10.1016\/j.cviu.2014.04.011","journal-title":"Comput. Vis. Image Underst."},{"key":"1699_CR7","doi-asserted-by":"publisher","unstructured":"Yew, Z.J., Lee, G.H.: Rpm-net: Robust point matching using learned features. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11821\u201311830 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.01184","DOI":"10.1109\/CVPR42600.2020.01184"},{"key":"1699_CR8","doi-asserted-by":"publisher","unstructured":"Fu, K., Liu, S., Luo, X., Wang, M.: Robust point cloud registration framework based on deep graph matching. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8889\u20138898 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00878","DOI":"10.1109\/CVPR46437.2021.00878"},{"issue":"1","key":"1699_CR9","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1111\/cgf.14715","volume":"42","author":"J Gao","year":"2023","unstructured":"Gao, J., Zhang, Y., Liu, Z., Li, S.: Hdrnet: High-dimensional regression network for point cloud registration. Comput. Graphics Forum 42(1), 33\u201346 (2023). https:\/\/doi.org\/10.1111\/cgf.14715","journal-title":"Comput. Graphics Forum"},{"key":"1699_CR10","unstructured":"Sarode, V., Li, X., Goforth, H., Aoki, Y., Srivatsan, R.A., Lucey, S., Choset, H.: Pcrnet: Point cloud registration network using pointnet encoding. arXiv preprint arXiv:1908.07906 (2019)"},{"key":"1699_CR11","doi-asserted-by":"crossref","unstructured":"Segal, A., Haehnel, D., Thrun, S.: Generalized-icp. In: Robotics: Science and Systems, vol. 2, p. 435 (2009). Seattle, WA","DOI":"10.15607\/RSS.2009.V.021"},{"key":"1699_CR12","doi-asserted-by":"crossref","unstructured":"Zhou, Q.-Y., Park, J., Koltun, V.: Fast global registration. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part II 14, pp. 766\u2013782 (2016). Springer","DOI":"10.1007\/978-3-319-46475-6_47"},{"key":"1699_CR13","doi-asserted-by":"publisher","unstructured":"Aoki, Y., Goforth, H., Srivatsan, R.A., Lucey, S.: Pointnetlk: Robust & efficient point cloud registration using pointnet. In: 2019 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7156\u20137165 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00733","DOI":"10.1109\/CVPR.2019.00733"},{"key":"1699_CR14","doi-asserted-by":"publisher","unstructured":"Chetverikov, D., Svirko, D., Stepanov, D., Krsek, P.: The trimmed iterative closest point algorithm. In: 2002 International Conference on Pattern Recognition, vol. 3, pp. 545\u20135483 (2002). https:\/\/doi.org\/10.1109\/ICPR.2002.1047997","DOI":"10.1109\/ICPR.2002.1047997"},{"issue":"5","key":"1699_CR15","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1111\/cgf.12178","volume":"32","author":"S Bouaziz","year":"2013","unstructured":"Bouaziz, S., Tagliasacchi, A., Pauly, M.: Sparse iterative closest point. Computer Graphics Forum 32(5), 113\u2013123 (2013). https:\/\/doi.org\/10.1111\/cgf.12178","journal-title":"Computer Graphics Forum"},{"key":"1699_CR16","doi-asserted-by":"crossref","unstructured":"Yuan, W., Eckart, B., Kim, K., Jampani, V., Fox, D., Kautz, J.: Deepgmr: Learning latent gaussian mixture models for registration. In: Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part V 16, pp. 733\u2013750 (2020). Springer","DOI":"10.1007\/978-3-030-58558-7_43"},{"key":"1699_CR17","doi-asserted-by":"crossref","unstructured":"Eckart, B., Kim, K., Kautz, J.: Hgmr: Hierarchical gaussian mixtures for adaptive 3d registration. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 705\u2013721 (2018)","DOI":"10.1007\/978-3-030-01267-0_43"},{"key":"1699_CR18","doi-asserted-by":"publisher","unstructured":"Yang, J., Li, H., Jia, Y.: Go-icp: Solving 3d registration efficiently and globally optimally. In: 2013 IEEE International Conference on Computer Vision, pp. 1457\u20131464 (2013). https:\/\/doi.org\/10.1109\/ICCV.2013.184","DOI":"10.1109\/ICCV.2013.184"},{"key":"1699_CR19","doi-asserted-by":"publisher","unstructured":"Li, X., Liu, Y., Xia, Y., Lakshminarasimhan, V., Cao, H., Zhang, F., Stilla, U., Knoll, A.: Fast and deterministic (3+1)dof point set registration with gravity prior. ISPRS Journal of Photogrammetry and Remote Sensing 199, 118\u2013132 (2023) https:\/\/doi.org\/10.1016\/j.isprsjprs.2023.03.022","DOI":"10.1016\/j.isprsjprs.2023.03.022"},{"issue":"2","key":"1699_CR20","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1109\/TRO.2020.3033695","volume":"37","author":"H Yang","year":"2021","unstructured":"Yang, H., Shi, J., Carlone, L.: Teaser: Fast and certifiable point cloud registration. IEEE Trans. Rob. 37(2), 314\u2013333 (2021). https:\/\/doi.org\/10.1109\/TRO.2020.3033695","journal-title":"IEEE Trans. Rob."},{"key":"1699_CR21","unstructured":"Srivatsan, R.A., Xu, M., Zevallos, N., Choset, H.: Bingham distribution-based linear filter for online pose estimation. In: Robotics: Science and Systems (2017). Robotics Science and Systems Foundation"},{"issue":"5","key":"1699_CR22","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1109\/34.765655","volume":"21","author":"AE Johnson","year":"1999","unstructured":"Johnson, A.E., Hebert, M.: Using spin images for efficient object recognition in cluttered 3d scenes. IEEE Trans. Pattern Anal. Mach. Intell. 21(5), 433\u2013449 (1999). https:\/\/doi.org\/10.1109\/34.765655","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1699_CR23","unstructured":"K\u00f6rtgen, M., Park, G.-J., Novotni, M., Klein, R.: 3d shape matching with 3d shape contexts. In: The 7th Central European Seminar on Computer Graphics, vol. 3, pp. 5\u201317 (2003). Budmerice Slovakia"},{"key":"1699_CR24","doi-asserted-by":"publisher","unstructured":"Choy, C., Park, J., Koltun, V.: Fully convolutional geometric features. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 8957\u20138965 (2019). https:\/\/doi.org\/10.1109\/ICCV.2019.00905","DOI":"10.1109\/ICCV.2019.00905"},{"key":"1699_CR25","doi-asserted-by":"publisher","unstructured":"Zeng, A., Song, S., Nie\u00dfner, M., Fisher, M., Xiao, J., Funkhouser, T.: 3dmatch: Learning local geometric descriptors from rgb-d reconstructions. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 199\u2013208 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.29","DOI":"10.1109\/CVPR.2017.29"},{"key":"1699_CR26","doi-asserted-by":"publisher","unstructured":"Gojcic, Z., Zhou, C., Wegner, J.D., Wieser, A.: The perfect match: 3d point cloud matching with smoothed densities. In: 2019 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 5540\u20135549 (2019). https:\/\/doi.org\/10.1109\/CVPR.2019.00569","DOI":"10.1109\/CVPR.2019.00569"},{"issue":"2","key":"1699_CR27","doi-asserted-by":"publisher","first-page":"2533","DOI":"10.1109\/LRA.2021.3061369","volume":"6","author":"H Zhao","year":"2021","unstructured":"Zhao, H., Liang, Z., Wang, C., Yang, M.: Centroidreg: A global-to-local framework for partial point cloud registration. IEEE Robot. Autom. Lett. 6(2), 2533\u20132540 (2021). https:\/\/doi.org\/10.1109\/LRA.2021.3061369","journal-title":"IEEE Robot. Autom. Lett."},{"key":"1699_CR28","doi-asserted-by":"publisher","unstructured":"Bai, X., Luo, Z., Zhou, L., Fu, H., Quan, L., Tai, C.-L.: D3feat: Joint learning of dense detection and description of 3d local features. In: 2020 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 6358\u20136366 (2020). https:\/\/doi.org\/10.1109\/CVPR42600.2020.00639","DOI":"10.1109\/CVPR42600.2020.00639"},{"key":"1699_CR29","doi-asserted-by":"publisher","unstructured":"Meng, L., Li, H., Chen, B.-C., Lan, S., Wu, Z., Jiang, Y.-G., Lim, S.-N.: Adavit: Adaptive vision transformers for efficient image recognition. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 12299\u201312308 (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.01199","DOI":"10.1109\/CVPR52688.2022.01199"},{"key":"1699_CR30","doi-asserted-by":"publisher","unstructured":"Ao, S., Hu, Q., Yang, B., Markham, A., Guo, Y.: Spinnet: Learning a general surface descriptor for 3d point cloud registration. In: 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11748\u201311757 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01158","DOI":"10.1109\/CVPR46437.2021.01158"},{"key":"1699_CR31","doi-asserted-by":"crossref","unstructured":"Du, J., Wang, R., Cremers, D.: Dh3d: Deep hierarchical 3d descriptors for robust large-scale 6dof relocalization. In: Vedaldi, H. Andreaand\u00a0Bischof, Brox, T., Frahm, J.-M. (eds.) Computer Vision \u2013 ECCV 2020, pp. 744\u2013762. Springer, Cham (2020)","DOI":"10.1007\/978-3-030-58548-8_43"},{"key":"1699_CR32","doi-asserted-by":"crossref","unstructured":"Xia, Y., Xu, Y., Li, S., Wang, R., Du, J., Cremers, D., Stilla, U.: Soe-net: A self-attention and orientation encoding network for point cloud based place recognition. 2021 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 11343\u201311352 (2020)","DOI":"10.1109\/CVPR46437.2021.01119"},{"key":"1699_CR33","doi-asserted-by":"publisher","unstructured":"Xia, Y., Gladkova, M., Wang, R., Li, Q., Stilla, U., Henriques, J.F., Cremers, D.: Casspr: Cross attention single scan place recognition. In: 2023 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 8427\u20138438 (2023). https:\/\/doi.org\/10.1109\/ICCV51070.2023.00777","DOI":"10.1109\/ICCV51070.2023.00777"},{"key":"1699_CR34","doi-asserted-by":"publisher","unstructured":"Charles, R.Q., Su, H., Kaichun, M., Guibas, L.J.: Pointnet: Deep learning on point sets for 3d classification and segmentation. In: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 77\u201385 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.16","DOI":"10.1109\/CVPR.2017.16"},{"key":"1699_CR35","doi-asserted-by":"crossref","unstructured":"Xu, H., Liu, S., Wang, G., Liu, G., Zeng, B.: Omnet: Learning overlapping mask for partial-to-partial point cloud registration. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 3132\u20133141 (2021)","DOI":"10.1109\/ICCV48922.2021.00312"},{"key":"1699_CR36","doi-asserted-by":"publisher","unstructured":"Wang, Y., Solomon, J.: Deep closest point: Learning representations for point cloud registration. In: 2019 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 3522\u20133531 (2019). https:\/\/doi.org\/10.1109\/ICCV.2019.00362","DOI":"10.1109\/ICCV.2019.00362"},{"key":"1699_CR37","doi-asserted-by":"crossref","unstructured":"Li, J., Zhang, C., Xu, Z., Zhou, H., Zhang, C.: Iterative distance-aware similarity matrix convolution with mutual-supervised point elimination for efficient point cloud registration. In: Computer Vision\u2013ECCV 2020: 16th European Conference, Glasgow, UK, August 23\u201328, 2020, Proceedings, Part XXIV 16, pp. 378\u2013394 (2020). Springer","DOI":"10.1007\/978-3-030-58586-0_23"},{"key":"1699_CR38","doi-asserted-by":"publisher","unstructured":"Lee, D., Hamsici, O.C., Feng, S., Sharma, P., Gernoth, T.: Deeppro: Deep partial point cloud registration of objects. In: 2021 IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 5663\u20135672 (2021). https:\/\/doi.org\/10.1109\/ICCV48922.2021.00563","DOI":"10.1109\/ICCV48922.2021.00563"},{"key":"1699_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, X., Yang, J., Zhang, S., Zhang, Y.: 3d registration with maximal cliques. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 17745\u201317754 (2023)","DOI":"10.1109\/CVPR52729.2023.01702"},{"key":"1699_CR40","doi-asserted-by":"crossref","unstructured":"Sarode, V., Dhagat, A., Srivatsan, R.A., Zevallos, N., Lucey, S., Choset, H.: Masknet: A fully-convolutional network to estimate inlier points. In: 2020 International Conference on 3D Vision (3DV), pp. 1029\u20131038 (2020). IEEE","DOI":"10.1109\/3DV50981.2020.00113"},{"key":"1699_CR41","doi-asserted-by":"crossref","unstructured":"Huang, S., Gojcic, Z., Usvyatsov, M., Wieser, A., Schindler, K.: Predator: Registration of 3d point clouds with low overlap. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 4267\u20134276 (2021)","DOI":"10.1109\/CVPR46437.2021.00425"},{"key":"1699_CR42","doi-asserted-by":"crossref","unstructured":"Qin, Z., Yu, H., Wang, C., Guo, Y., Peng, Y., Xu, K.: Geometric transformer for fast and robust point cloud registration. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 11143\u201311152 (2022)","DOI":"10.1109\/CVPR52688.2022.01086"},{"key":"1699_CR43","doi-asserted-by":"crossref","unstructured":"Yew, Z.J., Lee, G.H.: Regtr: End-to-end point cloud correspondences with transformers. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 6677\u20136686 (2022)","DOI":"10.1109\/CVPR52688.2022.00656"},{"key":"1699_CR44","doi-asserted-by":"crossref","unstructured":"Mei, G., Poiesi, F., Saltori, C., Zhang, J., Ricci, E., Sebe, N.: Overlap-guided gaussian mixture models for point cloud registration. In: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, pp. 4511\u20134520 (2023)","DOI":"10.1109\/WACV56688.2023.00449"},{"issue":"5","key":"1699_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3326362","volume":"38","author":"Y Wang","year":"2019","unstructured":"Wang, Y., Sun, Y., Liu, Z., Sarma, S.E., Bronstein, M.M., Solomon, J.M.: Dynamic graph cnn for learning on point clouds. ACM Trans. Gr. (tog) 38(5), 1\u201312 (2019)","journal-title":"ACM Trans. Gr. (tog)"},{"key":"1699_CR46","first-page":"2","volume":"32","author":"Y Wang","year":"2019","unstructured":"Wang, Y., Solomon, J.M.: Prnet: Self-supervised learning for partial-to-partial registration. Adv. Neural Inf. Process. Syst. 32, 2 (2019)","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"1699_CR47","doi-asserted-by":"publisher","unstructured":"Kadam, P., Zhang, M., Liu, S., Kuo, C.-C.J.: R-pointhop: A green, accurate, and unsupervised point cloud registration method. IEEE Trans. Image Process. 31, 2710\u20132725 (2022) https:\/\/doi.org\/10.1109\/TIP.2022.3160609","DOI":"10.1109\/TIP.2022.3160609"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-01699-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-025-01699-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-025-01699-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T19:35:30Z","timestamp":1745264130000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-025-01699-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,13]]},"references-count":47,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["1699"],"URL":"https:\/\/doi.org\/10.1007\/s00530-025-01699-4","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,13]]},"assertion":[{"value":"28 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 February 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"109"}}