{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T01:43:02Z","timestamp":1774575782409,"version":"3.50.1"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031723773","type":"print"},{"value":"9783031723780","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\/978-3-031-72378-0_40","type":"book-chapter","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T07:02:53Z","timestamp":1727852573000},"page":"430-436","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["HUP-3D: A 3D Multi-view Synthetic Dataset for\u00a0Assisted-Egocentric Hand-Ultrasound-Probe Pose Estimation"],"prefix":"10.1007","author":[{"given":"Manuel","family":"Birlo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Razvan","family":"Caramalau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philip J. \u201cEddie\u201d","family":"Edwards","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brian","family":"Dromey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthew J.","family":"Clarkson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danail","family":"Stoyanov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,3]]},"reference":[{"key":"40_CR1","doi-asserted-by":"crossref","unstructured":"Hasson, Y., Tekin, B., Bogo, F., Laptev, I., Pollefeys, M., Schmid, C.: Leveraging photometric consistency over time for sparsely supervised hand-object reconstruction. In: Proceedings of the IEEE\/CVF CVPR (June 2020)","DOI":"10.1109\/CVPR42600.2020.00065"},{"key":"40_CR2","doi-asserted-by":"crossref","unstructured":"Jiang, H., Liu, S., Wang, J., Wang, X.: Hand-Object Contact Consistency Reasoning for Human Grasps Generation. In: Proceedings of the ICCV (2021)","DOI":"10.1109\/ICCV48922.2021.01092"},{"key":"40_CR3","doi-asserted-by":"publisher","unstructured":"Akin, A., Erdede, E., Afshari, H., Schmid, A., Leblebici, Y.: Enhanced Omnidirectional Image Reconstruction Algorithm and Its Real-Time Hardware. In: Proceedings - 15th Euromicro Conference on Digital System Design, DSD 2012 (Sep 2012). https:\/\/doi.org\/10.1109\/DSD.2012.52. ISBN 978-1-4673-2498-4","DOI":"10.1109\/DSD.2012.52"},{"key":"40_CR4","doi-asserted-by":"crossref","unstructured":"Liu, S., Jiang, H., Xu, J., Liu, S., Wang, X.: Semi-supervised 3D hand-object poses estimation with interactions in time. In: Proceedings of the IEEE\/CVF CVPR, pp. 14687\u201314697 (June 2021)","DOI":"10.1109\/CVPR46437.2021.01445"},{"issue":"8","key":"40_CR5","doi-asserted-by":"publisher","first-page":"1898","DOI":"10.1109\/TPAMI.2019.2907951","volume":"42","author":"M Oberweger","year":"2020","unstructured":"Oberweger, M., Wohlhart, P., Lepetit, V.: Generalized Feedback Loop for Joint Hand-Object Pose Estimation. IEEE Trans. Pattern Anal. Mach. Intell. 42(8), 1898\u20131912 (2020). https:\/\/doi.org\/10.1109\/TPAMI.2019.2907951","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"40_CR6","doi-asserted-by":"crossref","unstructured":"Hasson, Y., et al.: Learning joint reconstruction of hands and manipulated objects. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2019)","DOI":"10.1109\/CVPR.2019.01208"},{"issue":"5","key":"40_CR7","doi-asserted-by":"publisher","first-page":"799","DOI":"10.1007\/s11548-021-02369-2","volume":"16","author":"J Hein","year":"2021","unstructured":"Hein, J., et al.: Towards markerless surgical tool and hand pose estimation. Inter. J. Comput. Assisted Radiol. Surgery 16(5), 799\u2013808 (2021). https:\/\/doi.org\/10.1007\/s11548-021-02369-2","journal-title":"Inter. J. Comput. Assisted Radiol. Surgery"},{"key":"40_CR8","doi-asserted-by":"crossref","unstructured":"Wang, R., Ktistakis, S., Zhang, S., Meboldt, M., Lohmeyer, Q.: POV-surgery: a dataset for egocentric hand and tool pose estimation during surgical activities. In: Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 440\u2013450 (2023)","DOI":"10.1007\/978-3-031-43996-4_42"},{"key":"40_CR9","doi-asserted-by":"crossref","unstructured":"Taheri, O., Ghorbani, N., Black, M.J., Tzionas, D.: GRAB: a dataset of whole-body human grasping of objects. In: Proceedings of the European Conference on Computer Vision (ECCV) (2020). https:\/\/grab.is.tue.mpg.de","DOI":"10.1007\/978-3-030-58548-8_34"},{"key":"40_CR10","doi-asserted-by":"crossref","unstructured":"Hampali, S., Rad, M., Oberweger, M., Lepetit, V.: HOnnotate: a method for 3D annotation of hand and object poses. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)","DOI":"10.1109\/CVPR42600.2020.00326"},{"key":"40_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1007\/978-3-030-58601-0_22","volume-title":"Computer Vision \u2013 ECCV 2020","author":"S Brahmbhatt","year":"2020","unstructured":"Brahmbhatt, S., Tang, C., Twigg, C.D., Kemp, C.C., Hays, J.: ContactPose: a dataset of grasps with object contact and hand pose. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.-M. (eds.) ECCV 2020. LNCS, vol. 12358, pp. 361\u2013378. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58601-0_22"},{"key":"40_CR12","doi-asserted-by":"crossref","unstructured":"Doosti, B., Naha, S., Mirbagheri, M., Crandall, D.J.: HOPE-net: a graph-based model for hand-object pose estimation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (June 2020)","DOI":"10.1109\/CVPR42600.2020.00664"},{"key":"40_CR13","doi-asserted-by":"crossref","unstructured":"Kwon, T., Tekin, B., St\u00fchmer, J., Bogo, F., Pollefeys, M.: H2O: Two hands manipulating objects for first person interaction recognition. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 10138\u201310148 (2021)","DOI":"10.1109\/ICCV48922.2021.00998"},{"issue":"4","key":"40_CR14","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1109\/MRA.2004.1371616","volume":"11","author":"AT Miller","year":"2004","unstructured":"Miller, A.T., Allen, P.K.: Graspit! a versatile simulator for robotic grasping. IEEE Robot. Autom. Mag. 11(4), 110\u2013122 (2004)","journal-title":"IEEE Robot. Autom. Mag."},{"key":"40_CR15","unstructured":"Blender Online Community: Blender - a 3D modelling and rendering package. Stichting Blender Foundation, Amsterdam (2018)"},{"issue":"6","key":"40_CR16","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1145\/3130800.3130883","volume":"36","author":"J Romero","year":"2017","unstructured":"Romero, J., Tzionas, D., Black, M.J.: Embodied hands: modeling and capturing hands and bodies together. ACM Trans. Graph. 36(6), 245 (2017)","journal-title":"ACM Trans. Graph."},{"key":"40_CR17","doi-asserted-by":"crossref","unstructured":"Dromey, B.P., et al.: Dimensionless squared jerk: An objective differential to assess experienced and novice probe movement in obstetric ultrasound. Prenatal Diagnosis 11 (2020)","DOI":"10.1002\/pd.5855"},{"key":"40_CR18","doi-asserted-by":"crossref","unstructured":"Cai, Y., et al.: Spatio-temporal visual attention modelling of standard biometry plane-finding navigation\u201d. Med. Image Anal. 65 (2020)","DOI":"10.1016\/j.media.2020.101762"},{"key":"40_CR19","doi-asserted-by":"crossref","unstructured":"Prokudin, S., Lassner, C., Romero, J.: Efficient learning on point clouds with basis point sets. In: Proceedings of the IEEE\/CVF ICCV (2019)","DOI":"10.1109\/ICCV.2019.00443"},{"key":"40_CR20","doi-asserted-by":"crossref","unstructured":"Varol, G.: Learning from synthetic humans. In: Proceedings of the IEEE CVPR (2017)","DOI":"10.1109\/CVPR.2017.492"},{"key":"40_CR21","doi-asserted-by":"crossref","unstructured":"Azari, D.P., Hu, Y.H., Miller, B.L., Le, B.V., Radwin, R.G.: Using surgeon hand motions to predict surgical maneuvers. Human Factors 61 (2019)","DOI":"10.1177\/0018720819838901"},{"key":"40_CR22","doi-asserted-by":"crossref","unstructured":"Zhou, X.-H., Bian, G.-B., Xie, X.-L., Hou, Z.-G., Qu, X., Guan, S.: Analysis of interventionalists natural behaviors for recognizing motion patterns of endovascular tools during percutaneous coronary interventions. IEEE Trans. Biomed. Circ. Syst. 13 (2019)","DOI":"10.1109\/TBCAS.2019.2892411"},{"key":"40_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/978-3-030-59716-0_56","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"R Droste","year":"2020","unstructured":"Droste, R., Drukker, L., Papageorghiou, A.T., Noble, J.A.: Automatic probe movement guidance for freehand obstetric ultrasound. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12263, pp. 583\u2013592. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59716-0_56"},{"key":"40_CR24","unstructured":"Goodman, E.D., et al.: A real-time spatiotemporal AI model analyzes skill in open surgical videos, arXiv preprint arXiv:2112.07219 (2021)"},{"key":"40_CR25","doi-asserted-by":"crossref","unstructured":"Jin, A., et al.: Tool detection and operative skill assessment in surgical videos using region-based convolutional neural networks. In: 2018 IEEE WACV (2018)","DOI":"10.1109\/WACV.2018.00081"},{"key":"40_CR26","doi-asserted-by":"crossref","unstructured":"Lajk\u00f3, G., Nagyn\u00e9 Elek, R., Haidegger, T.: Endoscopic image-based skill assessment in robot-assisted minimally invasive surgery. Sensors 21","DOI":"10.3390\/s21165412"},{"key":"40_CR27","doi-asserted-by":"crossref","unstructured":"Nguyen, T., Plishker, W., Matisoff, A., Sharma, K., Shekhar, R.: HoloUS: augmented reality visualization of live ultrasound images using hololens for ultrasound-guided procedures. Inter. J. Comput. Assisted Radiol. Surgery 17 (2022)","DOI":"10.1007\/s11548-021-02526-7"},{"key":"40_CR28","doi-asserted-by":"crossref","unstructured":"Romero, J., Tzionas, D., Black, M.J.: Embodied hands: modeling and capturing hands and bodies together. ACM Trans. Graph. Proc, SIGGRAPH Asia (2017)","DOI":"10.1145\/3130800.3130883"},{"key":"40_CR29","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep Residual Learning for Image Recognition, Tech Report, eprint=1512.03385 (2015)"},{"key":"40_CR30","doi-asserted-by":"crossref","unstructured":"Doosti, B., Naha, S., Mirbagheri, M., Crandall, D.: HOPE-net: a graph-based model for hand-object pose estimation. In: (CVPR) (June 2020)","DOI":"10.1109\/CVPR42600.2020.00664"},{"key":"40_CR31","unstructured":"Gao, H., Ji, S.: Graph U-Nets. In: ICML (2019)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72378-0_40","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T07:31:15Z","timestamp":1771054275000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72378-0_40"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031723773","9783031723780"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72378-0_40","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":"3 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"Author Danail Stoyanov is employed at Odin Vision Ltd. and Digital Surgery. Neither of these companies were involved in this publication. The other authors declare that they have no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","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":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}