Dear @3DTeethLandParticipants, We extend our heartfelt gratitude to all participants for their dedication and efforts in making the 3DTeethLand Challenge a success. Your hard work and innovative approaches have contributed significantly to advancing the field of 3D dental imaging ! And this is the final Leaderboard: {| class="border text-align-center" | Team | Rank Score | AP_cusp | AP_facial | AP_inner/outer | AP_mesial/distal | mAP | AR_cusp | AR_facial | AR_inner/outer | AR_mesial/distal | mAR | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | Radboud | 0.9172 | 0.772 | 0.768 | 0.793 | 0.792 | 0.785 | 0.675 | 0.637 | 0.661 | 0.651 | 0.656 | ChohoTech | 0.8325 | 0.765 | 0.761 | 0.78 | 0.781 | 0.775 | 0.627 | 0.586 | 0.625 | 0.672 | 0.634 | YY-LAB | 0.6224 | 0.684 | 0.726 | 0.748 | 0.705 | 0.719 | 0.719 | 0.569 | 0.601 | 0.576 | 0.579 | YN-LAB | 0.3171 | 0.656 | 0.667 | 0.61 | 0.657 | 0.643 | 0.538 | 0.522 | 0.511 | 0.539 | 0.527 | IGIP-LAB | 0.1358 | 0.636 | 0.59 | 0.634 | 0.523 | 0.59 | 0.519 | 0.445 | 0.505 | 0.41 | 0.466 | CG_sayaka | 0.1253 | 0.574 | 0.553 | 0.531 | 0.529 | 0.541 | 0.55 | 0.476 | 0.501 | 0.481 | 0.498 | 3DIMLAND | 0.0325 | 0.594 | 0.621 | 0.551 | 0.575 | 0.578 | 0.457 | 0.459 | 0.459 | 0.459 | 0.438 |} The ranking is based on the Wilcoxon Signed Rank Test, ensuring a statistically robust and fair evaluation of performance. Detailed information about the ranking process and metrics can be found [here](https://www.synapse.org/Synapse:syn57400900/wiki/627935) The evaluation code and ranking scripts are open-source and available to the public. We encourage everyone to explore and build upon them: [evaluation scripts](https://github.com/crns-smartvision/3DTeethLand/tree/master/evaluation) Congratulations to Team **Radboud** @nnistelrooij for securing the top position, and thank you to all teams for their outstanding contributions. We look forward to your continued innovations!