{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T23:07:15Z","timestamp":1768691235916,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":39,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819609161","type":"print"},{"value":"9789819609178","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T00:00:00Z","timestamp":1733616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,8]],"date-time":"2024-12-08T00:00:00Z","timestamp":1733616000000},"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\/978-981-96-0917-8_21","type":"book-chapter","created":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T08:00:41Z","timestamp":1733558441000},"page":"366-382","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Guide3D: A Bi-planar X-ray Dataset for\u00a03D Shape Reconstruction"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0324-0950","authenticated-orcid":false,"given":"Tudor","family":"Jianu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4421-652X","authenticated-orcid":false,"given":"Baoru","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9605-2939","authenticated-orcid":false,"given":"Hoan","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Binod","family":"Bhattarai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3290-3787","authenticated-orcid":false,"given":"Tuong","family":"Do","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6909-4623","authenticated-orcid":false,"given":"Erman","family":"Tjiputra","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5839-5875","authenticated-orcid":false,"given":"Quang","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9118-4877","authenticated-orcid":false,"given":"Pierre","family":"Berthet-Rayne","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2571-0511","authenticated-orcid":false,"given":"Ngan","family":"Le","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1006-4959","authenticated-orcid":false,"given":"Sebastiano","family":"Fichera","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1449-211X","authenticated-orcid":false,"given":"Anh","family":"Nguyen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,8]]},"reference":[{"key":"21_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultramic.2021.113460","volume":"234","author":"O Alting\u00f6vde","year":"2022","unstructured":"Alting\u00f6vde, O., Mishchuk, A., Ganeeva, G., Oveisi, E., Hebert, C., Fua, P.: 3d reconstruction of curvilinear structures with stereo matching deep convolutional neural networks. Ultramicroscopy 234, 113460 (2022)","journal-title":"Ultramicroscopy"},{"key":"21_CR2","doi-asserted-by":"crossref","unstructured":"Ambrosini, P., Ruijters, D., Niessen, W.J., Moelker, A., van Walsum, T.: Fully automatic and real-time catheter segmentation in x-ray fluoroscopy. In: International Conference on Medical Image Computing and Computer-Assisted Intervention (2017)","DOI":"10.1007\/978-3-319-66185-8_65"},{"key":"21_CR3","doi-asserted-by":"crossref","unstructured":"Ambrosini, P., Smal, I., Ruijters, D., Niessen, W.J., Moelker, A., van Walsum, T.: 3d catheter tip tracking in 2d x-ray image sequences using a hidden markov model and 3d rotational angiography. In: AE-CAI (2015)","DOI":"10.1007\/978-3-319-24601-7_5"},{"key":"21_CR4","doi-asserted-by":"crossref","unstructured":"Barbu, A., Athitsos, V., Georgescu, B., Boehm, S., Durlak, P., Comaniciu, D.: Hierarchical learning of curves application to guidewire localization in fluoroscopy. In: CVPR (2007)","DOI":"10.1109\/CVPR.2007.383033"},{"key":"21_CR5","doi-asserted-by":"crossref","unstructured":"Baur, C., Milletari, F., Belagiannis, V., Navab, N., Fallavollita, P.: Automatic 3d reconstruction of electrophysiology catheters from two-view monoplane c-arm image sequences. Int J Comput Assist Radiol Surg (2016)","DOI":"10.1007\/s11548-015-1325-8"},{"key":"21_CR6","doi-asserted-by":"crossref","unstructured":"Brainerd, E.L., Baier, D.B., Gatesy, S.M., Hedrick, T.L., Metzger, K.A., Gilbert, S.L., Crisco, J.J.: X-ray reconstruction of moving morphology (xromm): precision, accuracy and applications in comparative biomechanics research. J Exp Zool A Ecol Genet Physiol (2010)","DOI":"10.1002\/jez.589"},{"key":"21_CR7","doi-asserted-by":"crossref","unstructured":"Brost, A., Wimmer, A., Liao, R., Hornegger, J., Strobel, N.: Catheter tracking: Filter-based vs. learning-based. In: DAGM (2010)","DOI":"10.1007\/978-3-642-15986-2_30"},{"key":"21_CR8","doi-asserted-by":"crossref","unstructured":"Burgner, J., Herrell, S.D., Webster\u00a0III, R.J.: Toward fluoroscopic shape reconstruction for control of steerable medical devices. In: Dynamic Systems and Control Conference. vol. 54761, pp. 791\u2013794 (2011)","DOI":"10.1115\/DSCC2011-6029"},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Cao, H., Wang, Y., Chen, J., Jiang, D., Zhang, X., Tian, Q., Wang, M.: Swin-unet: Unet-like pure transformer for medical image segmentation. In: ECCV (2022)","DOI":"10.1007\/978-3-031-25066-8_9"},{"key":"21_CR10","unstructured":"Chen, J., Lu, Y., Yu, Q., Luo, X., Adeli, E., Wang, Y., Lu, L., Yuille, A.L., Zhou, Y.: Transunet: Transformers make strong encoders for medical image segmentation. arXiv (2021)"},{"key":"21_CR11","doi-asserted-by":"publisher","unstructured":"CVAT.ai Corporation: Computer vision annotation tool (cvat) (Nov 2023). https:\/\/doi.org\/10.5281\/zenodo.4009388, https:\/\/cvat.ai\/","DOI":"10.5281\/zenodo.4009388"},{"key":"21_CR12","doi-asserted-by":"crossref","unstructured":"Danilov, V.V., Kolpashchikov, D.Y., Gerget, O.M., Laptev, N.V., Proutski, A., G\u00f3mez, L.A.H., Alvarez, F., Ledesma-Carbayo, M.J.: Use of semi-synthetic data for catheter segmentation improvement. Comput Med Imaging Graph (2023)","DOI":"10.1016\/j.compmedimag.2023.102188"},{"key":"21_CR13","doi-asserted-by":"crossref","unstructured":"Delmas, C., Berger, M.O., Kerrien, E., Riddell, C., Trousset, Y., Anxionnat, R., Bracard, S.: Three-dimensional curvilinear device reconstruction from two fluoroscopic views. In: Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling. vol.\u00a09415, pp. 100\u2013110. Spie (2015)","DOI":"10.1117\/12.2081885"},{"key":"21_CR14","unstructured":"Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., et\u00a0al.: An image is worth 16x16 words: Transformers for image recognition at scale. arXiv preprint arXiv:2010.11929 (2020)"},{"key":"21_CR15","unstructured":"Dozat, T.: Incorporating nesterov momentum into adam. ICLR (Workshop) (2016)"},{"key":"21_CR16","unstructured":"Gailloud, P., Muster, M., Piotin, M., Mottu, F., Murphy, K.J., Fasel, J.H., R\u00fcfenacht, D.A.: In vitro models of intracranial arteriovenous fistulas for the evaluation of new endovascular treatment materials. AJNR (1999)"},{"key":"21_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1007\/978-3-642-33418-4_72","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2012","author":"M Hoffmann","year":"2012","unstructured":"Hoffmann, M., Brost, A., Jakob, C., Bourier, F., Koch, M., Kurzidim, K., Hornegger, J., Strobel, N.: Semi-automatic Catheter Reconstruction from Two Views. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012. LNCS, vol. 7511, pp. 584\u2013591. Springer, Heidelberg (2012). https:\/\/doi.org\/10.1007\/978-3-642-33418-4_72"},{"key":"21_CR18","doi-asserted-by":"crossref","unstructured":"Hoffmann, M., Brost, A., Jakob, C., Koch, M., Bourier, F., Kurzidim, K., Hornegger, J., Strobel, N.: Reconstruction method for curvilinear structures from two views. In: Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling. vol.\u00a08671, pp. 630\u2013637. Spie (2013)","DOI":"10.1117\/12.2006346"},{"issue":"2","key":"21_CR19","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1109\/TMI.2015.2482539","volume":"35","author":"M Hoffmann","year":"2015","unstructured":"Hoffmann, M., Brost, A., Koch, M., Bourier, F., Maier, A., Kurzidim, K., Strobel, N., Hornegger, J.: Electrophysiology catheter detection and reconstruction from two views in fluoroscopic images. IEEE Trans. Med. Imaging 35(2), 567\u2013579 (2015)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"21_CR20","doi-asserted-by":"crossref","unstructured":"Jianu, T., Huang, B., Vu, M.N., Abdelaziz, M.E., Fichera, S., Lee, C.Y., Berthet-Rayne, P., y\u00a0Baena, F.R., Nguyen, A.: Cathsim: An open-source simulator for endovascular intervention. IEEE T-MRB (2024)","DOI":"10.1109\/TMRB.2024.3421256"},{"issue":"2","key":"21_CR21","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1109\/TAC.1980.1102314","volume":"25","author":"V Klema","year":"1980","unstructured":"Klema, V., Laub, A.: The singular value decomposition: Its computation and some applications. IEEE Trans. Autom. Control 25(2), 164\u2013176 (1980)","journal-title":"IEEE Trans. Autom. Control"},{"key":"21_CR22","doi-asserted-by":"crossref","unstructured":"Ma, Y., King, A.P., Gogin, N., Rinaldi, C.A., Gill, J., Razavi, R., Rhode, K.S.: Real-time respiratory motion correction for cardiac electrophysiology procedures using image-based coronary sinus catheter tracking. In: MICCAI (2010)","DOI":"10.1007\/978-3-642-15705-9_48"},{"key":"21_CR23","unstructured":"Martin, J.B., Sayegh, Y., Gailloud, P., Sugiu, K., Khan, H.G., Fasel, J.H., R\u00fcfenacht, D.A.: In-vitro models of human carotid atheromatous disease. International Course Book of Peripheral Vascular Intervention (1998)"},{"key":"21_CR24","unstructured":"Mastmeyer, A., Pernelle, G., Barber, L., Pieper, S., Fortmeier, D., Wells, S., Handels, H., Kapur, T.: Model-based catheter segmentation in mri-images. arXiv (2017)"},{"key":"21_CR25","doi-asserted-by":"crossref","unstructured":"Nguyen, A., Kundrat, D., Dagnino, G., Chi, W., Abdelaziz, M.E., Guo, Y., Ma, Y., Kwok, T.M., Riga, C., Yang, G.Z.: End-to-end real-time catheter segmentation with optical flow-guided warping during endovascular intervention. In: ICRA. pp. 9967\u20139973. IEEE (2020)","DOI":"10.1109\/ICRA40945.2020.9197307"},{"key":"21_CR26","doi-asserted-by":"crossref","unstructured":"Petkovi\u0107, T., Homan, R., Lon\u010dari\u0107, S.: Real-time 3d position reconstruction of guidewire for monoplane x-ray. Comput Med Imaging Graph (2014)","DOI":"10.1016\/j.compmedimag.2013.12.006"},{"key":"21_CR27","doi-asserted-by":"publisher","unstructured":"P\u00fcschel, A., Schafmayer, C., Gro\u00df, J.: Robot-assisted techniques in vascular and endovascular surgery. Langenbecks Arch. Surg. , 1\u20137 (2022). https:\/\/doi.org\/10.1007\/s00423-022-02465-0","DOI":"10.1007\/s00423-022-02465-0"},{"key":"21_CR28","doi-asserted-by":"crossref","unstructured":"Rafii-Tari, H., Payne, C.J., Yang, G.Z.: Current and emerging robot-assisted endovascular catheterization technologies: a review. Ann Biomed Eng (2014)","DOI":"10.1007\/s10439-013-0946-8"},{"key":"21_CR29","doi-asserted-by":"crossref","unstructured":"Ramadani, A., Bui, M., Wendler, T., Schunkert, H., Ewert, P., Navab, N.: A survey of catheter tracking concepts and methodologies. Med Image Anal (2022)","DOI":"10.1016\/j.media.2022.102584"},{"key":"21_CR30","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: Convolutional networks for biomedical image segmentation. In: MICCAI (2015)","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"21_CR31","doi-asserted-by":"crossref","unstructured":"Sitzmann, V., Thies, J., Heide, F., Nie\u00dfner, M., Wetzstein, G., Zollhofer, M.: Deepvoxels: Learning persistent 3d feature embeddings. In: CVPR. pp. 2437\u20132446 (2019)","DOI":"10.1109\/CVPR.2019.00254"},{"key":"21_CR32","doi-asserted-by":"crossref","unstructured":"Subramanian, V., Wang, H., Wu, J.T., Wong, K.C., Sharma, A., Syeda-Mahmood, T.: Automated detection and type classification of central venous catheters in chest x-rays. In: MICCAI (2019)","DOI":"10.1007\/978-3-030-32226-7_58"},{"key":"21_CR33","unstructured":"Sutskever, I., Vinyals, O., Le, Q.V.: Sequence to sequence learning with neural networks. Advances in neural information processing systems 27 (2014)"},{"key":"21_CR34","doi-asserted-by":"crossref","unstructured":"Verdonck, B., Bourel, P., Coste, E., Gerritsen, F.A., Rousseau, J.: Variations in the geometrical distortion of x-ray image intensifiers. In: Physics of Medical Imaging (1999)","DOI":"10.1117\/12.349501"},{"issue":"3","key":"21_CR35","doi-asserted-by":"publisher","first-page":"1324","DOI":"10.1118\/1.4941950","volume":"43","author":"M Wagner","year":"2016","unstructured":"Wagner, M., Schafer, S., Strother, C., Mistretta, C.: 4d interventional device reconstruction from biplane fluoroscopy. Med. Phys. 43(3), 1324\u20131334 (2016)","journal-title":"Med. Phys."},{"key":"21_CR36","doi-asserted-by":"crossref","unstructured":"Wu, X., Housden, J., Ma, Y., Rhode, K., Rueckert, D.: A fast catheter segmentation and tracking from echocardiographic sequences based on corresponding x-ray fluoroscopic image segmentation and hierarchical graph modelling. In: ISBI (2014)","DOI":"10.1109\/ISBI.2014.6868029"},{"key":"21_CR37","doi-asserted-by":"crossref","unstructured":"Yi, X., Adams, S., Babyn, P., Elnajmi, A.: Automatic catheter and tube detection in pediatric x-ray images using a scale-recurrent network and synthetic data. JDI (2020)","DOI":"10.1007\/s10278-019-00201-7"},{"key":"21_CR38","doi-asserted-by":"publisher","DOI":"10.1109\/34.888718","volume-title":"A flexible new technique for camera calibration","author":"Z Zhang","year":"2000","unstructured":"Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach, Intell (2000)"},{"key":"21_CR39","volume-title":"A real-time multifunctional framework for guidewire morphological and positional analysis in interventional x-ray fluoroscopy","author":"YJ Zhou","year":"2020","unstructured":"Zhou, Y.J., Xie, X.L., Zhou, X.H., Liu, S.Q., Bian, G.B., Hou, Z.G.: A real-time multifunctional framework for guidewire morphological and positional analysis in interventional x-ray fluoroscopy. Trans. Cogn. Develop, Syst (2020)"}],"container-title":["Lecture Notes in Computer Science","Computer Vision \u2013 ACCV 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-0917-8_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T08:28:34Z","timestamp":1733560114000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-0917-8_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,8]]},"ISBN":["9789819609161","9789819609178"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-0917-8_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,8]]},"assertion":[{"value":"8 December 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ACCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Asian Conference on Computer Vision","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hanoi","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","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":"8 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"accv2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}