{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T18:01:22Z","timestamp":1785434482586,"version":"3.56.0"},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"32","license":[{"start":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:00:00Z","timestamp":1750204800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:00:00Z","timestamp":1750204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100010664","name":"H2020 Future and Emerging Technologies","doi-asserted-by":"publisher","award":["964854"],"award-info":[{"award-number":["964854"]}],"id":[{"id":"10.13039\/100010664","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-025-20918-8","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:57:30Z","timestamp":1750226250000},"page":"39577-39597","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Automatizing 3D reconstruction pipelines for speeding-up cultural heritage digitization"],"prefix":"10.1007","volume":"84","author":[{"given":"Gianluca","family":"Bison","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luca","family":"Palmieri","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sinem","family":"Aslan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7855-1641","authenticated-orcid":false,"given":"Sebastiano","family":"Vascon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcello","family":"Pelillo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"20918_CR1","unstructured":"Agisoft (2006) Agisoft Metashape. https:\/\/www.agisoft.com\/. Accessed 12 Nov 2024"},{"key":"20918_CR2","doi-asserted-by":"crossref","unstructured":"Aslan S, Pelillo M (2019) Weakly supervised semantic segmentation using constrained dominant sets. In: International conference on image analysis and processing, Springer, pp 425\u2013436","DOI":"10.1007\/978-3-030-30645-8_39"},{"key":"20918_CR3","doi-asserted-by":"crossref","unstructured":"Bai J, Wu X (2014) Error-tolerant scribbles based interactive image segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 392\u2013399","DOI":"10.1109\/CVPR.2014.57"},{"issue":"2","key":"20918_CR4","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"P Besl","year":"1992","unstructured":"Besl P, McKay ND (1992) A method for registration of 3-d shapes. IEEE Trans Pattern Anal Mach Intell 14(2):239\u2013256. https:\/\/doi.org\/10.1109\/34.121791","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"20918_CR5","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s11263-006-7934-5","volume":"70","author":"YFLG Boykov","year":"2006","unstructured":"Boykov YFLG (2006) Graph cuts and efficient n-d image segmentation. Int J Comput Vis 70:109\u2013131","journal-title":"Int J Comput Vis"},{"key":"20918_CR6","doi-asserted-by":"crossref","unstructured":"Brown BJ, Laken L, Dutr\u00e9 P, et al (2012) Tools for virtual reassembly of fresco fragments. International Journal of Heritage in the Digital Era 1(2)","DOI":"10.1260\/2047-4970.1.2.313"},{"key":"20918_CR7","doi-asserted-by":"publisher","unstructured":"Carsten G, Simone G, Lilian C, et al (2021) Alicevision meshroom: An open-source 3d reconstruction pipeline. In: Proc. 12th ACM Multimed. Syst. Conf. - MMSys \u201921. ACM Press. https:\/\/doi.org\/10.1145\/3458305.3478443","DOI":"10.1145\/3458305.3478443"},{"key":"20918_CR8","doi-asserted-by":"crossref","unstructured":"Cheng HK, Tai YW, Tang CK (2021a) Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 5559\u20135568","DOI":"10.1109\/CVPR46437.2021.00551"},{"key":"20918_CR9","first-page":"11781","volume":"34","author":"HK Cheng","year":"2021","unstructured":"Cheng HK, Tai YW, Tang CK (2021) Rethinking space-time networks with improved memory coverage for efficient video object segmentation. AdvNeural Inf Process Syst 34:11781\u201311794","journal-title":"AdvNeural Inf Process Syst"},{"key":"20918_CR10","doi-asserted-by":"crossref","unstructured":"Cheng MM, Prisacariu VA, Zheng S, et al (2015) Densecut: Densely connected crfs for realtime grabcut. In: Computer Graphics Forum, Wiley Online Library, pp 193\u2013201","DOI":"10.1111\/cgf.12758"},{"key":"20918_CR11","doi-asserted-by":"publisher","unstructured":"Chibane J, Alldieck T, Pons-Moll G (2020) Implicit functions in feature space for 3d shape reconstruction and completion. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 6968\u20136979. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00700","DOI":"10.1109\/CVPR42600.2020.00700"},{"key":"20918_CR12","doi-asserted-by":"crossref","unstructured":"Choy C, Park J, Koltun V (2019) Fully convolutional geometric features. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 8958\u20138966","DOI":"10.1109\/ICCV.2019.00905"},{"key":"20918_CR13","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.culher.2022.05.001","volume":"56","author":"L Di Angelo","year":"2022","unstructured":"Di Angelo L, Di Stefano P, Guardiani E (2022) A review of computer-based methods for classification and reconstruction of 3d high-density scanned archaeological pottery. J Cult Herit 56:10\u201324. https:\/\/doi.org\/10.1016\/j.culher.2022.05.001","journal-title":"J Cult Herit"},{"key":"20918_CR14","unstructured":"DJuri\u0107 I, Vasiljevi\u0107 I, Obradovi\u0107 M et al (2021) Comparative analysis of open-source and commercial photogrammetry software for cultural heritage. In: eCAADe 2021 International Scientific Conference, pp 8\u201310"},{"key":"20918_CR15","doi-asserted-by":"publisher","unstructured":"Genova K, Cole F, Sud A et al (2020) Local deep implicit functions for 3d shape. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 4856\u20134865. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00491","DOI":"10.1109\/CVPR42600.2020.00491"},{"key":"20918_CR16","doi-asserted-by":"crossref","unstructured":"Girshick R, Donahue J, Darrell T et al (2014) Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 580\u2013587","DOI":"10.1109\/CVPR.2014.81"},{"key":"20918_CR17","doi-asserted-by":"publisher","unstructured":"Griwodz C, Gasparini S, Calvet L et al (2021) Alicevision Meshroom: An open-source 3D reconstruction pipeline. In: Proceedings of the 12th ACM multimedia systems conference - MMSys \u201921. ACM Press, https:\/\/doi.org\/10.1145\/3458305.3478443","DOI":"10.1145\/3458305.3478443"},{"key":"20918_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jobe.2021.102690","volume":"44","author":"ME Hat\u0131r","year":"2021","unstructured":"Hat\u0131r ME, \u0130nce \u0130, Korkan\u00e7 M (2021) Intelligent detection of deterioration in cultural stone heritage. J Build Eng 44:102690","journal-title":"J Build Eng"},{"key":"20918_CR19","doi-asserted-by":"publisher","unstructured":"He K, Gkioxari G, Doll\u00e1r P et al (2017) Mask r-cnn. In: 2017 IEEE International Conference on Computer Vision (ICCV), pp 2980\u20132988. https:\/\/doi.org\/10.1109\/ICCV.2017.322","DOI":"10.1109\/ICCV.2017.322"},{"issue":"1","key":"20918_CR20","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1186\/s40494-024-01158-9","volume":"12","author":"M Hou","year":"2024","unstructured":"Hou M, Huo D, Yang Y et al (2024) Using mask r-cnn to rapidly detect the gold foil shedding of stone cultural heritage in images. Heritage Science 12(1):46","journal-title":"Heritage Science"},{"key":"20918_CR21","doi-asserted-by":"crossref","unstructured":"Huang S, Gojcic Z, Usvyatsov M et al (2021) 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","DOI":"10.1109\/CVPR46437.2021.00425"},{"key":"20918_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.sintl.2021.100114","volume":"2","author":"M Javaid","year":"2021","unstructured":"Javaid M, Haleem A, Pratap Singh R et al (2021) Industrial perspectives of 3d scanning: Features, roles and it\u2019s analytical applications. Sensors Int 2:100114. https:\/\/doi.org\/10.1016\/j.sintl.2021.100114","journal-title":"Sensors Int"},{"key":"20918_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.autcon.2023.104928","volume":"152","author":"X Kong","year":"2023","unstructured":"Kong X, Hucks RG (2023) Preserving our heritage: A photogrammetry-based digital twin framework for monitoring deteriorations of historic structures. Autom Constr 152:104928","journal-title":"Autom Constr"},{"key":"20918_CR24","doi-asserted-by":"crossref","unstructured":"Lin T, Maire M, Belongie SJ et al (2014) Microsoft COCO: common objects in context. CoRR arXiv:1405.0312","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"20918_CR25","doi-asserted-by":"crossref","unstructured":"Llull C, Baloian N, Bustos B et al (2023) Evaluation of 3d reconstruction for cultural heritage applications. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 1642\u20131651","DOI":"10.1109\/ICCVW60793.2023.00179"},{"issue":"5","key":"20918_CR26","doi-asserted-by":"publisher","first-page":"773","DOI":"10.3390\/rs16050773","volume":"16","author":"H Luo","year":"2024","unstructured":"Luo H, Zhang J, Liu X et al (2024) Large-scale 3d reconstruction from multi-view imagery: A comprehensive review. Remote Sensing 16(5):773","journal-title":"Remote Sensing"},{"issue":"1","key":"20918_CR27","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1145\/3503250","volume":"65","author":"B Mildenhall","year":"2021","unstructured":"Mildenhall B, Srinivasan PP, Tancik M et al (2021) Nerf: Representing scenes as neural radiance fields for view synthesis. Communications of the ACM 65(1):99\u2013106","journal-title":"Communications of the ACM"},{"key":"20918_CR28","doi-asserted-by":"crossref","unstructured":"Murez Z, van As T, Bartolozzi J et al (2020) Atlas: End-to-end 3d scene reconstruction from posed images. In: Vedaldi A, Bischof H, Brox T, et al (eds) European Conference on Computer Vision (ECCV), pp 414\u2013431","DOI":"10.1007\/978-3-030-58571-6_25"},{"issue":"3","key":"20918_CR29","doi-asserted-by":"publisher","first-page":"149","DOI":"10.3390\/info14030149","volume":"14","author":"A Osipov","year":"2023","unstructured":"Osipov A, Ostanin M, Klimchik A (2023) Comparison of point cloud registration algorithms for mixed-reality cross-device global localization. Information 14(3):149","journal-title":"Information"},{"issue":"1","key":"20918_CR30","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Transactions on Systems, Man, and Cybernetics 9(1):62\u201366. https:\/\/doi.org\/10.1109\/TSMC.1979.4310076","journal-title":"IEEE Transactions on Systems, Man, and Cybernetics"},{"key":"20918_CR31","doi-asserted-by":"crossref","unstructured":"Park JJ, Florence P, Straub J et al (2019) Deepsdf: Learning continuous signed distance functions for shape representation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 165\u2013174","DOI":"10.1109\/CVPR.2019.00025"},{"issue":"3","key":"20918_CR32","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1109\/MCG.2003.1198259","volume":"23","author":"M Pollefeys","year":"2003","unstructured":"Pollefeys M, Van Gool L, Vergauwen M et al (2003) 3d recording for archaeological fieldwork. IEEE Comput Graph Appl 23(3):20\u201327","journal-title":"IEEE Comput Graph Appl"},{"key":"20918_CR33","unstructured":"Polyga (2022) Polyga Flexscan 3D Software. https:\/\/www.polyga.com\/flexscan3d-software\/. Accessed 12 Nov 2024"},{"key":"20918_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.daach.2020.e00148","volume":"18","author":"R Quattrini","year":"2020","unstructured":"Quattrini R, Pierdicca R, Paolanti M et al (2020) Digital interaction with 3d archaeological artefacts: evaluating user\u2019s behaviours at different representation scales. Digital Applications in Archaeology and Cultural Heritage 18:e00148. https:\/\/doi.org\/10.1016\/j.daach.2020.e00148","journal-title":"Digital Applications in Archaeology and Cultural Heritage"},{"issue":"3","key":"20918_CR35","doi-asserted-by":"publisher","first-page":"1835","DOI":"10.3390\/heritage2030112","volume":"2","author":"H Rahaman","year":"2019","unstructured":"Rahaman H, Champion E (2019) To 3d or not 3d: Choosing a photogrammetry workflow for cultural heritage groups. Heritage 2(3):1835\u20131851. https:\/\/doi.org\/10.3390\/heritage2030112","journal-title":"Heritage"},{"key":"20918_CR36","unstructured":"Raytrix (2008) Inspection.https:\/\/raytrix.de\/inspection\/. Accessed 12 Nov 2024"},{"key":"20918_CR37","unstructured":"Ren S, He K, Girshick R et al (2015) Faster r-cnn: Towards real-time object detection with region proposal networks. Advances in neural information processing systems 28"},{"key":"20918_CR38","doi-asserted-by":"publisher","unstructured":"Rodr\u00edguez-Gonz\u00e1lvez P, Rodr\u00edguez-Mart\u00edn M, Ramos LF et al (2017) 3d reconstruction methods and quality assessment for visual inspection of welds. Automation in Construction 79:49\u201358. https:\/\/doi.org\/10.1016\/j.autcon.2017.03.002. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0926580517301863","DOI":"10.1016\/j.autcon.2017.03.002"},{"key":"20918_CR39","doi-asserted-by":"crossref","unstructured":"Rodriguez-Garcia B, Guillen-Sanz H, Checa D et al (2024) A systematic review of virtual 3d reconstructions of cultural heritage in immersive virtual reality. Multimedia Tools and Applications pp 1\u201351","DOI":"10.1007\/s11042-024-18700-3"},{"key":"20918_CR40","first-page":"234","volume-title":"Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation. In: Navab N, Hornegger J, Wells WM et al (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015. Springer International Publishing, Cham, pp 234\u2013241"},{"key":"20918_CR41","doi-asserted-by":"publisher","unstructured":"Rusinkiewicz S, Levoy M (2001) Efficient variants of the icp algorithm. In: Proceedings third international conference on 3-D digital imaging and modeling, pp 145\u2013152. https:\/\/doi.org\/10.1109\/IM.2001.924423","DOI":"10.1109\/IM.2001.924423"},{"key":"20918_CR42","doi-asserted-by":"publisher","unstructured":"Rusu RB, Blodow N, Beetz M (2009) Fast point feature histograms (fpfh) for 3d registration. In: 2009 IEEE international conference on robotics and automation, pp 3212\u20133217. https:\/\/doi.org\/10.1109\/ROBOT.2009.5152473","DOI":"10.1109\/ROBOT.2009.5152473"},{"key":"20918_CR43","doi-asserted-by":"crossref","unstructured":"Schonberger JL, Frahm JM (2016) Structure-from-motion revisited. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4104\u20134113","DOI":"10.1109\/CVPR.2016.445"},{"key":"20918_CR44","doi-asserted-by":"crossref","unstructured":"Sch\u00f6nberger JL, Zheng E, Frahm JM et al (2016) Pixelwise view selection for unstructured multi-view stereo. In: 14th European conference on computer vision (ECCV 2016), Amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part III 14, Springer, pp 501\u2013518","DOI":"10.1007\/978-3-319-46487-9_31"},{"key":"20918_CR45","doi-asserted-by":"crossref","unstructured":"Sofiiuk K, Petrov I, Barinova O et al (2020a) f-brs: Rethinking backpropagating refinement for interactive segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8623\u20138632","DOI":"10.1109\/CVPR42600.2020.00865"},{"key":"20918_CR46","doi-asserted-by":"crossref","unstructured":"Sofiiuk K, Petrov I, Barinova O et al (2020b) f-brs: Rethinking backpropagating refinement for interactive segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 8623\u20138632","DOI":"10.1109\/CVPR42600.2020.00865"},{"key":"20918_CR47","doi-asserted-by":"crossref","unstructured":"Sofiiuk K, Petrov I, Konushin A (2021) Reviving iterative training with mask guidance for interactive segmentation. arXiv:2102.06583","DOI":"10.1109\/ICIP46576.2022.9897365"},{"key":"20918_CR48","doi-asserted-by":"crossref","unstructured":"Sofiiuk K, Petrov IA, Konushin A (2022) Reviving iterative training with mask guidance for interactive segmentation. In: 2022 IEEE International conference on image processing (ICIP), IEEE, pp 3141\u20133145","DOI":"10.1109\/ICIP46576.2022.9897365"},{"key":"20918_CR49","unstructured":"Theoharis T, Papaioannou G, Bj\u00f8rlykke K et al (2013) Multi-scale 3d digitization at nidaros cathedral: from archiving to large-scale visualization. In: 18th Conference on cultural heritage and new technologies"},{"key":"20918_CR50","unstructured":"Tsesmelis T, Palmieri L, Khoroshiltseva M et al (2024) Re-assembling the past: The repair dataset and benchmark for real world 2d and 3d puzzle solving. arXiv:2410.24010 Project page: https:\/\/repairproject.github.io\/RePAIR_dataset\/"},{"key":"20918_CR51","doi-asserted-by":"crossref","unstructured":"Wang J, Zhang C, Wang P et al (2023) Batch-based model registration for fast 3d sherd reconstruction. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp 14519\u201314529","DOI":"10.1109\/ICCV51070.2023.01335"},{"key":"20918_CR52","doi-asserted-by":"publisher","unstructured":"Wang Y, Solomon J (2019) Deep closest point: Learning representations for point cloud registration. In: 2019 IEEE\/CVF lion (ICCV), pp 3522\u20133531. https:\/\/doi.org\/10.1109\/ICCV.2019.00362","DOI":"10.1109\/ICCV.2019.00362"},{"issue":"2","key":"20918_CR53","doi-asserted-by":"publisher","first-page":"314","DOI":"10.1109\/TRO.2020.3033695","volume":"37","author":"H Yang","year":"2020","unstructured":"Yang H, Shi J, Carlone L (2020) Teaser: Fast and certifiable point cloud registration. IEEE Trans Robot 37(2):314\u2013333","journal-title":"IEEE Trans Robot"},{"key":"20918_CR54","doi-asserted-by":"crossref","unstructured":"Yavartanoo M, Chung J, Neshatavar R et al (2021) 3dias: 3d shape reconstruction with implicit algebraic surfaces. In: Proceedings of the IEEE\/CVF international conference on computer vision (ICCV), pp 12446\u201312455","DOI":"10.1109\/ICCV48922.2021.01222"},{"key":"20918_CR55","doi-asserted-by":"crossref","unstructured":"Zemene E, Pelillo M (2016) Interactive image segmentation using constrained dominant sets. In: Computer vision\u2013ECCV 2016: 14th european conference, amsterdam, The Netherlands, October 11-14, 2016, Proceedings, Part VIII 14, Springer, pp 278\u2013294","DOI":"10.1007\/978-3-319-46484-8_17"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-025-20918-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-025-20918-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-025-20918-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T15:12:32Z","timestamp":1758899552000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-025-20918-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,18]]},"references-count":55,"journal-issue":{"issue":"32","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["20918"],"URL":"https:\/\/doi.org\/10.1007\/s11042-025-20918-8","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,18]]},"assertion":[{"value":"25 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 April 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 May 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All authors have given their consent for the publication","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for Publication"}}]}}