{"url":"/dataset/teeth3ds","name":"Teeth3DS+","full_name":"An Extended Benchmark for Intraoral 3D Scans Analysis","description_markdown":"Intraoral 3D scans analysis is a fundamental aspect of Computer-Aided Dentistry (CAD) systems,\r\nplaying a crucial role in various dental applications, including teeth segmentation, detection, labeling,\r\nand dental landmark identification. Accurate analysis of 3D dental scans is essential for orthodontic and prosthetic treatment planning, as it enables automated processing and reduces the need for\r\nmanual adjustments by dental professionals. However, developing robust automated tools for these\r\ntasks remains a significant challenge due to the limited availability of high-quality public datasets and\r\nbenchmarks. This article introduces Teeth3DS+, the first comprehensive public benchmark designed\r\nto advance the field of intraoral 3D scan analysis. Developed as part of the 3DTeethSeg 2022 and\r\n3DTeethLand 2024 MICCAI challenges, Teeth3DS+ aims to drive research in teeth identification, segmentation, labeling, 3D modeling, and dental landmarks identification. The dataset includes at least\r\n1,800 intraoral scans (containing 23,999 annotated teeth) collected from 900 patients, covering both\r\nupper and lower jaws separately. All data have been acquired and validated by experienced orthodontists and dental surgeons with over five years of expertise. Detailed instructions for accessing the\r\ndataset are available at https://crns-smartvision.github.io/teeth3ds","description_withheld":null,"homepage":"https://crns-smartvision.github.io/teeth3ds","introduced_date":"2022-10-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/teeth3ds-a-benchmark-for-teeth-segmentation","title":"Teeth3DS+: An Extended Benchmark for Intraoral 3D Scans Analysis","first_author":"Achraf Ben-Hamadou","url":null},"license":{"name":"CC BY-NC-ND 4.0","url":"https://creativecommons.org/licenses/by-nc-nd/4.0/"},"modalities":[{"name":"Point cloud","url":"/datasets/modality/point-cloud"},{"name":"3d meshes","url":"/datasets/modality/3d-meshes"}],"tasks":[{"name":"3D Point Cloud Classification","url":"/task/3d-point-cloud-classification","datasets_with_task":"/datasets/task/3d-point-cloud-classification"},{"name":"3D Classification","url":"/task/3d-classification","datasets_with_task":"/datasets/task/3d-classification"},{"name":"3D Part Segmentation","url":"/task/3d-part-segmentation","datasets_with_task":"/datasets/task/3d-part-segmentation"}],"languages":[],"variants":["Teeth3DS+"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}