ODIN2025 - Oral and Dental Image aNalysis challenges

Computer-aided diagnosis tools are increasingly popular in modern dental practice, particularly for treatment planning or comprehensive prognosis evaluation [1*]. In dental applications, Cone-Beam Computed Tomography (CBCT) and Intra-oral Scan (IOS) are 3D imaging techniques widely used for surgical planning and simulation [2*, 3*, 4*]. CBCT provides information on dental and maxillofacial structures, whereas IOS provides highly accurate surface information on tooth crowns and gingiva surfaces. In particular, segmentation of anatomical structures (e.g., teeth, pharynx, mandible) from CBCT and registration between CBCT and IOS is an essential prerequisite for surgical planning for dental implants or orthognathic surgery [1*, 5*]. Although the medical imaging community has proposed many solutions, these methods are trained and verified on a small, often private, amount of data, and their performances do not meet clinical requirements.

The main objective of our challenges is to push further the research on 3D dental image analysis, applying the rigorous approaches to performance evaluation needed in the medical field and calling for the latest results and techniques, which are often neglected by application-specific papers.

Our ODIN2025 initiative brings together two different challenge series, ToothFairy, and 3DTeethSeg, combining most of the image modalities involved in maxillofacial analysis, i.e., CBCTs and IOSs. Building on the success of our previous initiatives, with ODIN2025 we aim to further advance the understanding of cone beam computed tomography and intra-oral scans, addressing more complex data and structures and increasing the amount of training and testing sets. An ever-increasing effort in this edition is put into the clinical applicability of the participant solutions by considering not only performance but also typical constraints of daily clinical practice: time and resources.

Through this collaborative effort, we aim to pave the way for future multimodal image analysis that can more accurately and efficiently inform clinical decision-making, from diagnostics to treatment planning and post-surgical evaluations. The continued advancement in 3D dental imaging, along with improved segmentation, registration, and integration of CBCT and IOS data, holds the potential to revolutionize the way dental procedures are performed, ultimately benefiting both patients and practitioners alike.

[1*] Cui, Z., Fang, Y., Mei, L., Zhang, B., Yu, B., Liu, J., Jiang, C., Sun, Y., Ma, L., Huang, J., et al.: A fully automatic AI system for tooth and alveolar bone segmentation from cone-beam CT images. Nature Communications 13(1), 2096 (2022) 1
[2*] Flügge, T., Derksen, W., Te Poel, J., Hassan, B., Nelson, K., Wismeijer, D.: Registration of cone beam computed tomography data and intraoral surface scans–a prerequisite for guided implant surgery with cad/cam drilling guides. Clinical Oral Implants Research 28(9), 1113–1118 (2017) 1
[3*] Jamjoom, F.Z., Kim, D.G., McGlumphy, E.A., Lee, D.J., Yilmaz, B.: Positional accuracy of a prosthetic treatment plan incorporated into a cone beam computed tomography scan using surface scan registration. The Journal of Prosthetic Dentistry 120(3), 367–374 (2018) 1
[4*] Kim, S., Choi, Y., Na, J., Song, I.S., Lee, Y.S., Hwang, B.Y., Lim, H.K., Baek, S.J.: Best of both modalities: Fusing CBCT and intraoral scan data into a single tooth image. In: International Conference on Medical Image  Computing and Computer-Assisted Intervention. pp. 553–563. Springer (2024
[5*] Rangel, F.A., Maal, T.J., de Koning, M.J., Bronkhorst, E.M., Berg´e, S.J., Kuijpers-Jagtman, A.M.: Integration of digital dental casts in cone beam computed tomography scans—a clinical validation study. Clinical Oral Investigations 22, 1215–1222 (2018).

* Shared first authors: Federico Bolelli, Achraf Ben-Hamadou