20 citations · 39 across the 7 of their papers we have counts for
5 papers · 1 filter
Detecting Dental Landmarks from Intraoral 3D Scans: the 3DTeethLand challenge
Achraf Ben-Hamadou, Nour Neifar, Ahmed Rekik +23
Teeth landmark detection is a key task in modern orthodontics, supporting advanced diagnosis, personalized treatment planning, and effective monitoring of treatment progress. Howev…
Artificial Intelligence to Assess Dental Findings from Panoramic Radiographs -- A Multinational Study
Yin-Chih Chelsea Wang, Tsao-Lun Chen, Shankeeth Vinayahalingam +13
Dental panoramic radiographs (DPRs) are widely used in clinical practice for comprehensive oral assessment but present challenges due to overlapping structures and time constraints…
Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps
Florian Kofler, Hendrik Möller, Josef A. Buchner +18
This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. p…
Fully automated landmarking and facial segmentation on 3D photographs
Bo Berends, Freek Bielevelt, Ruud Schreurs +3
Three-dimensional facial stereophotogrammetry provides a detailed representation of craniofacial soft tissue without the use of ionizing radiation. While manual annotation of landm…
3DTeethSeg'22: 3D Teeth Scan Segmentation and Labeling Challenge
Achraf Ben-Hamadou, Oussama Smaoui, Ahmed Rekik +29
Teeth localization, segmentation, and labeling from intra-oral 3D scans are essential tasks in modern dentistry to enhance dental diagnostics, treatment planning, and population-ba…