{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T11:58:05Z","timestamp":1781006285809,"version":"3.54.1"},"reference-count":26,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T00:00:00Z","timestamp":1780617600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Romanian Hub for Artificial Intelligence-HRIA","award":["351416, PNRR-III-C9-2023-I8"],"award-info":[{"award-number":["351416, PNRR-III-C9-2023-I8"]}]},{"name":"Technologically Enabled Advancements in Dental Medicine","award":["100418\/29.08.2025"],"award-info":[{"award-number":["100418\/29.08.2025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Dentistry Journal"],"abstract":"<jats:p>Background\/Objectives: Dynamic navigation and robot-assisted implant workflows depend on robust intraoral perception. Marker-based tracking introduces workflow complexity and is sensitive to occlusions, motivating markerless alternatives. This study evaluates whether a single-stage YOLO instance segmentation model (YOLO-seg) can provide a practical markerless perception layer for dental navigation, combining accurate per-tooth delineation with low, predictable inference latency. Methods: YOLO-seg was trained end to end on an intraoral RGB corpus of 400 training, 20 validation, and 100 testing images, combining a public source and a partner-hospital in-house set. A two-stage YOLO + SAM baseline was implemented for comparison. Segmentation quality was evaluated on a 50-image held-out clinical test set at three complementary levels (per-instance matching, per-class union, and global union), with paired Wilcoxon signed-rank tests, Cliff\u2019s delta effect sizes, and 95% bootstrap confidence intervals. Runtime was assessed under matched inference-only and end-to-end conditions on N = 100 frames at a 640 \u00d7 640 resolution on an NVIDIA RTX A2000 GPU. Results: YOLO-seg significantly outperformed YOLO + SAM across all primary metrics, with very large effect sizes (Cliff\u2019s delta: 0.76\u20130.94; Wilcoxon p &lt; 10\u22128 on every metric except precision at IoU \u2265 0.5). YOLO-seg reached AP50 = 0.716 and recall = 0.973 versus 0.383 and 0.398 for YOLO + SAM. Under matched inference-only timing, YOLO-seg ran at 27.08 ms per frame (36.9 FPS) versus 1302.78 ms (0.77 FPS), an approximately 48-fold latency gap intrinsic to the two-stage forward pass. Conclusions: YOLO-seg shows strong potential as a 2D perception module for dental navigation, balancing per-instance segmentation fidelity with real-time feasibility under the tested conditions. These results support its use as a 2D perception front-end for future integration with stereo-based 3D reconstruction and robot-assisted navigation; 3D registration accuracy, implant-placement error, and robotic execution remain outside the scope of the present study.<\/jats:p>","DOI":"10.3390\/dj14060345","type":"journal-article","created":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T17:18:16Z","timestamp":1780679896000},"page":"345","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Real-Time Markerless Tooth Detection Towards Dynamic Robot-Assisted Dental Implant Navigation"],"prefix":"10.3390","volume":"14","author":[{"given":"Vasile","family":"Bulbucan","sequence":"first","affiliation":[{"name":"CESTER, (Research Center for Industrial Robots Simulation and Testing), Department of Mechanical Systems Engineering, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania"},{"name":"European University of Technology, European Union"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8866-4662","authenticated-orcid":false,"given":"Daria","family":"Pisla","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Oral Radiology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5660-8259","authenticated-orcid":false,"given":"Paul","family":"Tucan","sequence":"additional","affiliation":[{"name":"CESTER, (Research Center for Industrial Robots Simulation and Testing), Department of Mechanical Systems Engineering, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania"},{"name":"European University of Technology, European Union"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1073-9402","authenticated-orcid":false,"given":"Cristian","family":"Dinu","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Maxillofacial Surgery and Implantology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400429 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2822-9790","authenticated-orcid":false,"given":"Calin","family":"Vaida","sequence":"additional","affiliation":[{"name":"CESTER, (Research Center for Industrial Robots Simulation and Testing), Department of Mechanical Systems Engineering, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania"},{"name":"European University of Technology, European Union"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rares","family":"Mocan","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Oral Radiology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mihaela","family":"Baciut","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Maxillofacial Surgery and Implantology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400429 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5708-0780","authenticated-orcid":false,"given":"Sebastian","family":"Stoia","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Maxillofacial Surgery and Implantology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400429 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mihaela","family":"Hedesiu","sequence":"additional","affiliation":[{"name":"Department of Maxillofacial Surgery and Radiology, Oral Radiology, \u201cIuliu Hatieganu\u201d University of Medicine and Pharmacy, 400006 Cluj-Napoca, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0483-7691","authenticated-orcid":false,"given":"Ionut","family":"Zima","sequence":"additional","affiliation":[{"name":"CESTER, (Research Center for Industrial Robots Simulation and Testing), Department of Mechanical Systems Engineering, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania"},{"name":"European University of Technology, European Union"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7014-9431","authenticated-orcid":false,"given":"Doina","family":"Pisla","sequence":"additional","affiliation":[{"name":"CESTER, (Research Center for Industrial Robots Simulation and Testing), Department of Mechanical Systems Engineering, Faculty of Industrial Engineering, Robotics and Production Management, Technical University of Cluj-Napoca, 28 Memorandumului Street, 400114 Cluj-Napoca, Romania"},{"name":"European University of Technology, European Union"},{"name":"Technical Sciences Academy of Romania, B-dul Dacia, 26, 030167 Bucharest, Romania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"TEAM Project Group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pisla, D., Bulbucan, V., Hedesiu, M., Vaida, C., Pusca, A., Mocan, R., Tucan, P., Dinu, C., and Pisla, D. (2025). Accuracy of Navigation and Robot-Assisted Systems for Dental Implant Placement: A Systematic Review. Dent. J., 13.","DOI":"10.3390\/dj13110537"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Kafedzhieva, A., Vlahova, A., and Chuchulska, B. (2025). Digital Technologies in Implantology: A Narrative Review. Bioengineering, 12.","DOI":"10.3390\/bioengineering12090927"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"104567","DOI":"10.1016\/j.jdent.2023.104567","article-title":"Accuracy assessment of dynamic navigation during implant placement: A systematic review and meta-analysis of clinical studies in the last 10 years","volume":"135","author":"Yu","year":"2023","journal-title":"J. Dent."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"91.e1","DOI":"10.1016\/j.prosdent.2025.03.038","article-title":"Accuracy in dental implant placement: A systematic review and meta-analysis comparing computer-assisted (static, dynamic, robotics) and noncomputer-assisted (freehand, conventional guide) approaches","volume":"134","author":"Khaohoen","year":"2025","journal-title":"J. Prosthet. Dent."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"212","DOI":"10.1109\/RBME.2019.2939091","article-title":"Optical and Electromagnetic Tracking Systems for Biomedical Applications: A Critical Review on Potentialities and Limitations","volume":"13","author":"Sorriento","year":"2020","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"120743","DOI":"10.1016\/j.eswa.2023.120743","article-title":"An intelligent tracking system for surgical instruments in complex surgical environment","volume":"230","author":"Chen","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Pisla, D., Bulbucan, V., Hede\u0219iu, M., Vaida, C., Cailean, A., Mocan, R., Tucan, P., Dinu, C., Pisla, D., and TEAM Project Group (2025). Real-Time Motion Compensation for Dynamic Dental Implant Surgery. J. Clin. Med., 14.","DOI":"10.3390\/jcm14186429"},{"key":"ref_8","first-page":"2255","article-title":"A Systematic Review of YOLO-Based Object Detection in Medical Imaging: Advances, Challenges, and Future Directions","volume":"85","author":"Cai","year":"2025","journal-title":"Comput. Mater. Contin."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Ali, M.L., and Zhang, Z. (2024). The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection. Computers, 13.","DOI":"10.20944\/preprints202410.1785.v1"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., and Lo, W.-Y. (2023). Segment Anything. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), IEEE. Available online: https:\/\/openaccess.thecvf.com\/content\/ICCV2023\/html\/Kirillov_Segment_Anything_ICCV_2023_paper.html.","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Pandey, S., Chen, K.-F., and Dam, E.B. (2023). Comprehensive Multimodal Segmentation in Medical Imaging: Combining YOLOv8 with SAM and HQ-SAM Models. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) Workshops, IEEE.","DOI":"10.1109\/ICCVW60793.2023.00273"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"292","DOI":"10.1007\/s44163-026-00930-z","article-title":"Exploring YOLO applications in dentistry through a systematic review of detection and segmentation models","volume":"6","author":"Hartman","year":"2026","journal-title":"Discov. Artif. Intell."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Bonfanti-Gris, M., Herrera, A., Rodr\u00edguez-Manzaneque, M.P.S., Mart\u00ednez-Rus, F., and Prad\u00edes, G. (2025). Deep learning for tooth detection and segmentation in panoramic radiographs: A systematic review and meta-analysis. BMC Oral Health, 25.","DOI":"10.1186\/s12903-025-06349-9"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"557","DOI":"10.20517\/ais.2025.92","article-title":"Deep learning in real-time image-guided surgery: A systematic review of applications, methodologies, and clinical relevance","volume":"5","author":"Kasimieh","year":"2025","journal-title":"Artif. Intell. Surg."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2513","DOI":"10.1007\/s11548-025-03480-4","article-title":"Towards a zero-shot low-latency navigation for open surgery augmented reality applications","volume":"20","author":"Schwimmbeck","year":"2025","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1110","DOI":"10.1016\/j.jds.2025.01.003","article-title":"SegmentAnyTooth: An open-source deep learning framework for tooth enumeration and segmentation in intraoral photos","volume":"20","author":"Nguyen","year":"2025","journal-title":"J. Dent. Sci."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1038\/s41467-024-44824-z","article-title":"Segment anything in medical images","volume":"15","author":"Ma","year":"2024","journal-title":"Nat. Commun."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Pisla, D., Bulbucan, V., Hedesiu, M., Vaida, C., Zima, I., Mocan, R., Tucan, P., Dinu, C., Pisla, D., and TEAM Project Group (2024). A Vision-Guided Robotic System for Safe Dental Implant Surgery. J. Clin. Med., 13.","DOI":"10.3390\/jcm13216326"},{"key":"ref_19","unstructured":"(2026, January 26). Ultralytics, Ultralytics Data Overview. Available online: https:\/\/docs.ultralytics.com\/datasets\/."},{"key":"ref_20","unstructured":"(2026, February 13). Ultralytics, Instance Segmentation Datasets Overview. Available online: https:\/\/docs.ultralytics.com\/datasets\/segment\/."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., and Farhadi, A. (2016). You Only Look Once: Unified, Real-Time Object Detection. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), IEEE. Available online: https:\/\/www.cv-foundation.org\/openaccess\/content_cvpr_2016\/html\/Redmon_You_Only_Look_CVPR_2016_paper.html.","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref_22","first-page":"1","article-title":"Statistical Comparisons of Classifiers over Multiple Data Sets","volume":"7","year":"2006","journal-title":"J. Mach. Learn. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1037\/0033-2909.114.3.494","article-title":"Dominance Statistics: Ordinal Analyses to Answer Ordinal Questions","volume":"114","author":"Cliff","year":"1993","journal-title":"Psychol. Bull."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Rahbar, M.D., Pappas, G., and Jaber, N. (2024). Toward Intraoperative Visual Intelligence: Real-Time Surgical Instrument Segmentation for Enhanced Surgical Monitoring. Healthcare, 12.","DOI":"10.3390\/healthcare12111112"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhou, L., Wu, G., Zuo, Y., Chen, X., and Hu, H. (2024). A Comprehensive Review of Vision-Based 3D Reconstruction Methods. Sensors, 24.","DOI":"10.3390\/s24072314"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"032001","DOI":"10.1088\/2516-1091\/ad525b","article-title":"Tackling the small data problem in medical image classification with artificial intelligence: A systematic review","volume":"6","author":"Piffer","year":"2024","journal-title":"Prog. Biomed. Eng."}],"container-title":["Dentistry Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2304-6767\/14\/6\/345\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T11:02:45Z","timestamp":1781002965000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2304-6767\/14\/6\/345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,5]]},"references-count":26,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["dj14060345"],"URL":"https:\/\/doi.org\/10.3390\/dj14060345","relation":{},"ISSN":["2304-6767"],"issn-type":[{"value":"2304-6767","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,5]]}}}