{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T04:03:15Z","timestamp":1743134595868,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031723520"},{"type":"electronic","value":"9783031723537"}],"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\/978-3-031-72353-7_18","type":"book-chapter","created":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T15:04:02Z","timestamp":1726499042000},"page":"245-259","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CurSegNet: 3D Dental Model Segmentation Network Based on\u00a0Curve Feature Aggregation"],"prefix":"10.1007","author":[{"given":"Jiafa","family":"Mao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhan","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingke","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunping","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sixian","family":"Chan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,17]]},"reference":[{"issue":"10","key":"18_CR1","doi-asserted-by":"publisher","first-page":"13275","DOI":"10.1007\/s11042-021-10536-5","volume":"81","author":"S Chan","year":"2022","unstructured":"Chan, S., Huang, C., Bai, C., Ding, W., Chen, S.: Res2-UNeXt: a novel deep learning framework for few-shot cell image segmentation. Multimedia Tools Appl. 81(10), 13275\u201313288 (2022). https:\/\/doi.org\/10.1007\/s11042-021-10536-5","journal-title":"Multimedia Tools Appl."},{"key":"18_CR2","doi-asserted-by":"crossref","unstructured":"Chan, S., Wang, Y., Lei, Y., Cheng, X., Chen, Z., Wu, W.: Asymmetric cascade fusion network for building extraction. IEEE Trans. Geoscience Remote Sens. (2023)","DOI":"10.1109\/TGRS.2023.3306018"},{"key":"18_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107487","volume":"166","author":"S Chan","year":"2023","unstructured":"Chan, S., Wu, B., Wang, H., Zhou, X., Zhang, G., Wang, G.: Cross-domain mechanism for few-shot object detection on urine sediment image. Comput. Biol. Med. 166, 107487 (2023)","journal-title":"Comput. Biol. Med."},{"key":"18_CR4","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1007\/s41095-021-0229-5","volume":"7","author":"MH Guo","year":"2021","unstructured":"Guo, M.H., Cai, J.X., Liu, Z.N., Mu, T.J., Martin, R.R., Hu, S.M.: PCT: point cloud transformer. Comput. Vis. Media 7, 187\u2013199 (2021)","journal-title":"Comput. Vis. Media"},{"key":"18_CR5","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"issue":"3","key":"18_CR6","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1109\/TMI.2004.824235","volume":"23","author":"T Kondo","year":"2004","unstructured":"Kondo, T., Ong, S.H., Foong, K.W.: Tooth segmentation of dental study models using range images. IEEE Trans. Med. Imaging 23(3), 350\u2013362 (2004)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"18_CR7","unstructured":"Li, Y., Bu, R., Sun, M., Wu, W., Di, X., Chen, B.: PointCNN: convolution on X-transformed points. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"18_CR8","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1007\/978-3-030-32226-7_93","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13\u201317, 2019, Proceedings, Part VI","author":"C Lian","year":"2019","unstructured":"Lian, C., et al.: MeshSNet: deep multi-scale mesh feature learning for end-to-end tooth labeling on 3D dental surfaces. In: Shen, D., et al. (eds.) Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13\u201317, 2019, Proceedings, Part VI, pp. 837\u2013845. Springer International Publishing, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32226-7_93"},{"key":"18_CR9","unstructured":"Ma, X., Qin, C., You, H., Ran, H., Fu, Y.: Rethinking network design and local geometry in point cloud: a simple residual MLP framework. arXiv preprint arXiv:2202.07123 (2022)"},{"key":"18_CR10","doi-asserted-by":"crossref","unstructured":"Maturana, D., Scherer, S.: VoxNet: a 3D convolutional neural network for real-time object recognition. In: 2015 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 922\u2013928. IEEE (2015)","DOI":"10.1109\/IROS.2015.7353481"},{"key":"18_CR11","unstructured":"Qi, C.R., Su, H., Mo, K., Guibas, L.J.: PointNet: deep learning on point sets for 3d classification and segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 652\u2013660 (2017)"},{"key":"18_CR12","doi-asserted-by":"crossref","unstructured":"Qi, C.R., Su, H., Nie\u00dfner, M., Dai, A., Yan, M., Guibas, L.J.: Volumetric and multi-view CNNs for object classification on 3D data. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5648\u20135656 (2016)","DOI":"10.1109\/CVPR.2016.609"},{"key":"18_CR13","unstructured":"Qi, C.R., Yi, L., Su, H., Guibas, L.J.: PointNet++: deep hierarchical feature learning on point sets in a metric space. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Sinthanayothin, C., Tharanont, W.: Orthodontics treatment simulation by teeth segmentation and setup. In: 2008 5th International Conference on Electrical Engineering\/Electronics, Computer, Telecommunications and Information Technology, vol.\u00a01, pp. 81\u201384. IEEE (2008)","DOI":"10.1109\/ECTICON.2008.4600377"},{"key":"18_CR15","doi-asserted-by":"crossref","unstructured":"Su, H., Maji, S., Kalogerakis, E., Learned-Miller, E.: Multi-view convolutional neural networks for 3D shape recognition. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 945\u2013953 (2015)","DOI":"10.1109\/ICCV.2015.114"},{"key":"18_CR16","doi-asserted-by":"publisher","first-page":"84817","DOI":"10.1109\/ACCESS.2019.2924262","volume":"7","author":"S Tian","year":"2019","unstructured":"Tian, S., Dai, N., Zhang, B., Yuan, F., Yu, Q., Cheng, X.: Automatic classification and segmentation of teeth on 3D dental model using hierarchical deep learning networks. IEEE Access 7, 84817\u201384828 (2019)","journal-title":"IEEE Access"},{"issue":"5","key":"18_CR17","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. Graph. (TOG) 38(5), 1\u201312 (2019)","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"18_CR18","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.cag.2013.10.028","volume":"38","author":"K Wu","year":"2014","unstructured":"Wu, K., Chen, L., Li, J., Zhou, Y.: Tooth segmentation on dental meshes using morphologic skeleton. Comput. Graph. 38, 199\u2013211 (2014)","journal-title":"Comput. Graph."},{"key":"18_CR19","doi-asserted-by":"crossref","unstructured":"Wu, W., Qi, Z., Fuxin, L.: PointConv: deep convolutional networks on 3D point clouds. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9621\u20139630 (2019)","DOI":"10.1109\/CVPR.2019.00985"},{"key":"18_CR20","doi-asserted-by":"crossref","unstructured":"Xiang, T., Zhang, C., Song, Y., Yu, J., Cai, W.: Walk in the cloud: learning curves for point clouds shape analysis. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 915\u2013924 (2021)","DOI":"10.1109\/ICCV48922.2021.00095"},{"key":"18_CR21","unstructured":"Zanjani, F.G., Moin, D.A., Verheij, B., Claessen, F., Cherici, T., Tan, T., et\u00a0al.: Deep learning approach to semantic segmentation in 3D point cloud intra-oral scans of teeth. In: International Conference on Medical Imaging with Deep Learning, pp. 557\u2013571. PMLR (2019)"},{"key":"18_CR22","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.compbiomed.2014.10.013","volume":"56","author":"BJ Zou","year":"2015","unstructured":"Zou, B.J., Liu, S.J., Liao, S.H., Ding, X., Liang, Y.: Interactive tooth partition of dental mesh base on tooth-target harmonic field. Comput. Biol. Med. 56, 132\u2013144 (2015)","journal-title":"Comput. Biol. Med."}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72353-7_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T15:20:50Z","timestamp":1726500050000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72353-7_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031723520","9783031723537"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72353-7_18","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"17 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lugano","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Switzerland","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":"17 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"33","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}