3D Teeth Scan Segmentation and Labeling Challenge¶
We strongly recommend you visit: https://github.com/abenhamadou/3DTeethSeg22_challenge
This page will no longer be maintained. (This includes join requests and leaderboard)
To request access to the data, kindly refer to the instructions provided on the git repository of the challenge.
The challenge 3DTeethSeg22 is a first edition associated with MICCAI 2022. It is organized by Udini (France) in collaboration with Inria Grenoble Morpheo team (France) and the Digital Research Center of Sfax (Tunisia).
Computer-aided design (CAD) tools have become increasingly popular in modern dentistry for highly accurate treatment planning. In particular, in orthodontic CAD systems, advanced intraoral scanners (IOSs) are now widely used as they provide precise digital surface models of the dentition. Such models can dramatically help dentists simulate teeth extraction, move, deletion, and rearrangement and ease therefore the prediction of treatment outcomes. Hence, digital teeth models have the potential to release dentists from otherwise tedious and time consuming tasks.
Although IOSs are becoming widespread in clinical dental practice, there are only few contributions on teeth segmentation/labeling available in the literature and no publicly available database. A fundamental issue that appears with IOS data is the ability to reliably segment and identify teeth in scanned observations. Teeth segmentation and labeling is difficult as a result of the inherent similarities between teeth shapes as well as their ambiguous positions on jaws.
In addition, it faces several challenges:
- The teeth position and shape variation across subjects.
- The presence of abnormalities in dentition. For example, teeth crowding which results in teeth misalignment and thus non-explicit boundaries between neighboring teeth. Moreover, lacking teeth and holes are commonly seen among people.
- Damaged teeth.
- The presence of braces, and other dental equipment
The challenge we propose will particularly focus on point 1, i.e. the teeth position and shape variation across subjects. With the extension of available data in the mid and long term, the other points will also be addressed in further editions of the challenge.
How to participate¶
Individuals or team members interested in participating in this challenge should carefully study the challenge rules and then follow these steps:
- Register on the grand-challenge website via this link.
- Sign in to your account and revisit the challenge webpage.
- Click on the green "Join" bottom on the top right corner of the webpage.
After completing these three steps, you will be forwarded to the challenge registration page where you will need to submit your request. Once your participation request has been accepted, you will have access to the data download and submission pages.
*Please note that by participating in this challenge you are agreeing to all its rules and policies.
On the grand-challenge platform, algorithms can be created by submitting a docker image, or a github repository from which the image can be built. Submissions to 3DTeethSeg22 are only accepted in form of a grand-challenge algorithm. Full instructions on how this can be done, as well as template repositories are provided. Once you have successfully created an algorithm it can be submitted to the corresponding track on the Submit page. The participant models will run on a machine with NVIDIA T4 GPU.
To access code and example notebooks relating to the challenge, take a look at our GitHub page.
Prizes¶
coming soon [ongoing negotiation with potential sponsors]¶
Authorship¶
We plan to invite at least three solutions from each track based on their final performance, their methodology and the write-up provided by the authors for inclusion in a peer-reviewed article about the challenge. For this article, we will include additional experiments. These methods will be selected to ensure diversity of methodology as well as excellent performance. The authors of the selected algorithms (maximum of three authors per algorithm) will be invited to be a co-author of the 3DTeethSeg22 overview article which will be submitted to a high-impact journal.
