{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T18:48:15Z","timestamp":1785178095670,"version":"3.55.0"},"reference-count":21,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,14]],"date-time":"2021-11-14T00:00:00Z","timestamp":1636848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Sichuan Science and Technology Program","award":["2021YFQ0003"],"award-info":[{"award-number":["2021YFQ0003"]}]}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Sensors"],"abstract":"<jats:p>At present, feature-based 3D reconstruction and tracking technology is widely applied in the medical field. In minimally invasive surgery, the surgeon can achieve three-dimensional reconstruction through the images obtained by the endoscope in the human body, restore the three-dimensional scene of the area to be operated on, and track the motion of the soft tissue surface. This enables doctors to have a clearer understanding of the location depth of the surgical area, greatly reducing the negative impact of 2D image defects and ensuring smooth operation. In this study, firstly, the 3D coordinates of each feature point are calculated by using the parameters of the parallel binocular endoscope and the spatial geometric constraints. At the same time, the discrete feature points are divided into multiple triangles using the Delaunay triangulation method. Then, the 3D coordinates of feature points and the division results of each triangle are combined to complete the 3D surface reconstruction. Combined with the feature matching method based on convolutional neural network, feature tracking is realized by calculating the three-dimensional coordinate changes of the same feature point in different frames. Finally, experiments are carried out on the endoscope image to complete the 3D surface reconstruction and feature tracking.<\/jats:p>","DOI":"10.3390\/s21227570","type":"journal-article","created":{"date-parts":[[2021,11,14]],"date-time":"2021-11-14T20:51:53Z","timestamp":1636923113000},"page":"7570","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Study on Reconstruction and Feature Tracking of Silicone Heart 3D Surface"],"prefix":"10.3390","volume":"21","author":[{"given":"Ziyan","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Innovation and Entrepreneurship, Xi\u2019an Fanyi University, Xi\u2019an 710105, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1407-0283","authenticated-orcid":false,"given":"Yan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6398-7461","authenticated-orcid":false,"given":"Jiawei","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8040-0367","authenticated-orcid":false,"given":"Shan","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Longhai","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5022-610X","authenticated-orcid":false,"given":"Lirong","family":"Yin","sequence":"additional","affiliation":[{"name":"Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70803, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8486-1654","authenticated-orcid":false,"given":"Wenfeng","family":"Zheng","sequence":"additional","affiliation":[{"name":"School of Automation, University of Electronic Science and Technology of China, Chengdu 610054, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1109\/JBHI.2014.2384134","article-title":"Stitching and Surface Reconstruction From Endoscopic Image Sequences: A Review of Applications and Methods","volume":"20","author":"Bergen","year":"2016","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"e2015.00052","DOI":"10.4293\/JSLS.2015.00052","article-title":"Past, Present, and Future of Minimally Invasive Abdominal Surgery","volume":"19","author":"Antoniou","year":"2015","journal-title":"JSLS J. Soc. Laparoendosc. Surg."},{"key":"ref_3","first-page":"1","article-title":"Image-guided procedures: A review","volume":"3","author":"Yaniv","year":"2006","journal-title":"Comput. Aided Interv. Med. Robot."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"368","DOI":"10.4253\/wjge.v9.i8.368","article-title":"Evolution of stereoscopic imaging in surgery and recent advances","volume":"9","author":"Schwab","year":"2017","journal-title":"World J. Gastrointest. Endosc."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/s10462-012-9329-z","article-title":"Surface reconstruction techniques: A review","volume":"42","author":"Lim","year":"2014","journal-title":"Artif. Intell. Rev."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1007\/s00371-016-1316-y","article-title":"A survey on algorithms of hole filling in 3D surface reconstruction","volume":"34","author":"Guo","year":"2018","journal-title":"Vis. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Paoli, A., Neri, P., Razionale, A.V., Tamburrino, F., and Barone, S. (2020). Sensor Architectures and Technologies for Upper Limb 3D Surface Reconstruction: A Review. Sensors, 20.","DOI":"10.3390\/s20226584"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1111\/cgf.12802","article-title":"A Survey of Surface Reconstruction from Point Clouds","volume":"36","author":"Berger","year":"2017","journal-title":"Comput. Graph. Forum"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1578","DOI":"10.1109\/TPAMI.2019.2954885","article-title":"Image-Based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era","volume":"43","author":"Han","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1109\/TMI.2019.2927436","article-title":"Real-Time Dense Reconstruction of Tissue Surface from Stereo Optical Video","volume":"39","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.cmpb.2018.02.006","article-title":"SLAM-based dense surface reconstruction in monocular Minimally Invasive Surgery and its application to Augmented Reality","volume":"158","author":"Chen","year":"2018","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.aei.2018.05.005","article-title":"A review of 3D reconstruction techniques in civil engineering and their applications","volume":"37","author":"Ma","year":"2018","journal-title":"Adv. Eng. Inform."},{"key":"ref_13","unstructured":"Wu, X., Xiao, S., and Wei, J. (2015, January 6\u20139). High accurate 3D reconstruction method using binocular stereo based on multiple constraints. Proceedings of the 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Joo, H., Simon, T., and Sheikh, Y. (2018, January 18\u201323). Total capture: A 3d deformation model for tracking faces, hands, and bodies. Proceedings of the 2018 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, UT, USA.","DOI":"10.1109\/CVPR.2018.00868"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Yang, Q., Engels, C., and Akbarzadeh, A. (2008, January 1\u20134). Near Real-time Stereo for Weakly-Textured Scenes. Proceedings of the 2008 BMVC, Leeds, UK.","DOI":"10.5244\/C.22.72"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1632","DOI":"10.1118\/1.3681017","article-title":"Dense GPU-enhanced surface reconstruction from stereo endoscopic images for intraoperative registration","volume":"39","author":"Bodenstedt","year":"2012","journal-title":"Med. Phys."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"15635","DOI":"10.1007\/s11042-015-2845-5","article-title":"Binocular vision calibration and 3D re-construction with an orthogonal learning neural network","volume":"75","author":"Ge","year":"2015","journal-title":"Multimed. Tools Appl."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1109\/LRA.2017.2735487","article-title":"Dynamic Reconstruction of Deformable Soft-Tissue With Stereo Scope in Minimal Invasive Surgery","volume":"3","author":"Song","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"550","DOI":"10.1016\/j.media.2011.02.010","article-title":"Context specific descriptors for tracking deforming tissue","volume":"16","author":"Mountney","year":"2012","journal-title":"Med. Image Anal."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1109\/TPAMI.2012.81","article-title":"Probabilistic Tracking of Affine-Invariant Anisotropic Regions","volume":"35","author":"Giannarou","year":"2012","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"6222","DOI":"10.1364\/BOE.9.006222","article-title":"Reconstructing a 3D heart surface with stereo-endoscope by learning eig-en-shapes","volume":"9","author":"Yang","year":"2018","journal-title":"Biomed. Opt. Express"}],"updated-by":[{"DOI":"10.3390\/s26154753","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2021,11,14]],"date-time":"2021-11-14T00:00:00Z","timestamp":1636848000000}}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7570\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,27]],"date-time":"2026-07-27T13:31:29Z","timestamp":1785159089000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/22\/7570"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,14]]},"references-count":21,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["s21227570"],"URL":"https:\/\/doi.org\/10.3390\/s21227570","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,14]]}}}