Dental Radiography and Imaging

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• EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

  Ruiyang Hao, Zhi Qin Tan, Yulan He, Owen Addison, Yunpeng Li · 5 octobre 2026

  Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning to generate such reports from limited clinical data is challenging because routine reports may not exhaustively document image findings, and a non-me…

• Detection is solved, delineation is not: what governs tooth segmentation on panoramic radiographs

  Muhammad Rehan, Moaz Amjad, Syed Danial Ahmed, Mariam Adnan, Haider Ali · 21 septembre 2026

  Automatic tooth segmentation and FDI numbering on panoramic radiographs underpins computer-assisted dental diagnosis, yet which factors govern performance remains unclear. We assemble a corpus of 1,422 panoramic radiographs containing 42,142 expert-delineated tooth polygons across the 32-class FDI t…

• Predicting build orientation for SLM dental parts: a comparison of rotation representations and direct vector regression

  Felix Schmalzel, Reimar Waitz, Moritz Kronberger, Thorsten Sch\"oler · 15 septembre 2026

  Build orientation for selective laser melting (SLM) manufacturing of dental parts is usually chosen manually by technicians. We treat orientation prediction as supervised machine learning of the part's up-axis from technician-labeled production data, and test which rotation representations produce t…

• Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion

  Zhichun Jin, Zhicheng He, Hao Xu, Dongyang Li, Lin Wang, Hongliang Ren, Long Bai · 10 septembre 2026

  Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed tomography (CBCT) is used for visual measurement, and the reconstructed lateral cephalograms are handed over to expert dentists for diagnosis. However…

• Entity-Constrained CBCT Retrieval for Low-Resource Dental Record Completion

  Nhi Ngoc-Yen Nguyen, Thai Nguyen, Kiet Huynh Cao Tuan, Huy-Hieu Pham · 25 août 2026

  Completing dental records from cone-beam computed tomography (CBCT) is difficult when annotation is scarce and individual clinical fields are supported by different types of evidence. MMDental Task 3 requires seven-field record completion from only 50 labeled CBCT cases and scores the correctness of…

• Topology of a Smile: Persistent Homology in Dental Imaging

  Leon Dahlmeier, Sara Kali\v{s}nik, Albert Mehl, Bastian Rieck · 25 août 2026

  CBCT (Cone Beam Computed Tomography) scans provide detailed three-dimensional images, widely used in dentistry for diagnostic and treatment planning tasks. While invaluable, analyzing and documenting these scans is labor-intensive, prompting efforts to automate key steps like the classification and …

• Teeth2Point: A Two-Stage Dental CBCT ROI-to-Point Segmentation Framework

  Qi Ma, Shipra Jain, Niko Benjamin Huber, Ender Konukoglu · 20 août 2026

  Modern deep learning architectures have demonstrated strong performance in dental CBCT segmentation. One remaining crucial challenge is accurate tooth labeling in cases with missing or malpositioned teeth, which are highly relevant for dental practice. Transformer-based architectures should in theor…

• DentAgent: Evidence-Centric Multi-Agent Coordination for Multimodal Dental Reasoning

  Zijie Meng, Xiwei Dai, Yixuan Tang, Jin Hao, Yang Feng, Fudong Zhu, Xiaoqiang Liu, Shaosheng Cao, Zuozhu Liu · 20 août 2026

  Oral diseases affect billions of people worldwide, underscoring a pressing need for accurate and reliable dental assessment that integrates heterogeneous evidence from domain knowledge, radiographs, intraoral photographs, and 3D dental data. Most existing dental AI systems remain modality- or task-s…

• B-Spline Embedded Structure Learning for 3D Tooth Segmentation

  Xianghan Wei, Jianwen Lou, Zhiguo Lu, Hairong Jin, Haihua Zhu · 19 août 2026

  Accurate 3D tooth segmentation forms the cornerstone of digital dentistry, yet it remains a formidable challenge due to the inherent intricacy of real-world dentitions, such as crowding, misaligned teeth and high morphological similarity between adjacent teeth. To resolve this, we present B-Spline E…

• Automatic Cephalometric Landmark Localization on CBCT-Derived Digitally Reconstructed Radiographs for Skeletal Malocclusion Classification

  Benjamin Hou, Konstantinia Almpani, Janice S. Lee, Zhiyong Lu · 18 août 2026

  Manual cephalometric landmark annotation is important for craniofacial assessment but is labor-intensive and difficult to scale. We introduce CephViT, a Vision Transformer-based model for automated 2D lateral cephalometric landmark localization, and evaluate its use in downstream skeletal malocclusi…

• Surface-to-Skeleton 3D Cephalometry: Estimating Hidden Skeletal Landmarks from CT-Derived External Soft-Tissue Surfaces

  Tomoki Abe, Taiki Kanaya, Kazuki Saita, Mao Noda, Chie Tachiki, Yasushi Nishii, Hideo Saito · 14 août 2026

  Existing 3D facial-landmark methods localize points on visible skin, but whether CT-defined internal skeletal landmarks can be inferred from external soft-tissue geometry remains unclear. We formulate a coordinate-consistent surface-to-skeleton task using same-acquisition CT-derived surfaces, separa…

• Coarse-to-Fine Registration of Jawbone CT and Intraoral Scan Data Using GeDi and ICP with Pseudo-IOS Ground Truth

  Sho Mitarai, Hikaru Kayo, Hisashi Ozaki, Yuichiro Imai, Megumi Nakao · 11 août 2026

  In digital dentistry and oral surgery, the registration of jawbone CT and intraoral scanner (IOS) data is essential for integrating internal bone structure with high-resolution dental surface geometry. However, this registration is challenging because the two modalities share only a limited region i…

• APCReg: Anatomical-Prior-Guided Coarse-to-Fine CBCT--IOS Registration via Multi-View Projection and Reliability-Controlled Residual Correction

  Xincan Zheng, Yaqi Wang, Zhi Li, Jiahao Bao, Lan Feng, Yiru Xia, Shuai Wang · 10 août 2026

  Registration between cone-beam computed tomography (CBCT) and intraoral scans (IOS) is essential for patient-specific surgical planning. However, disparate imaging modalities, limited overlap, and large pose offsets make automated registration unreliable. Consequently, clinical registration remains …

• TLNM: Externally Validated Tooth Detection, Numbering and Segmentation from Smartphone Photographs Using Mask R-CNN

  Arash Nedaei, Henna Tiensuu, Elina Väyrynen, Saujanya Karki, Jaakko Suutala · 7 août 2026

  Oral health issues affect billions globally, but the cost and limited access to professional dental care hinder preventive oral healthcare. Research relies on clinical-grade radiographs or intraoral camera images, unavailable for public self-screening. This study introduces a tooth localisation and …

• PanDent: Toward Comprehensive Tooth-Level Structure-Language Consistency in Dental Radiology

  Xiaohan Li, Xinyu Liu, Chang Liu, Sum Wing Au Yeung, Jun Liu, Yixuan Yuan, Hui Chen · 31 juillet 2026

  Accurate evaluation of multimodal large language models (MLLMs) in dental panoramic radiography (orthopantomogram, OPG) is limited by the lack of fine-grained, clinically reliable benchmarks that reflect expert interpretation. This work introduces PanDent, a large-scale, clinically grounded OPG benc…

• X-Splat: Gaussian Splatting for 3D CBCT Generation from Single Panoramic Radiograph

  Tomasz Szczepański, Szymon Płotka, Michal K. Grzeszczyk, Tomasz Trzciński, Arkadiusz Sitek · 3 juillet 2026

  Generating a 3D dental volume from a single panoramic radiograph (PXR) could provide a low-radiation alternative to Cone-Beam Computed Tomography (CBCT), but the problem is highly underdetermined: panoramic acquisition integrates 3D attenuation along curved X-ray paths into a 2D image, leaving depth…

• Self-Supervised Vision Transformers for CBCT-Based Detection of Temporomandibular Joint Osteoarthritis

  Shradhdha Trivedi, Vrundan Sojitra, Mariela Padilla · 9 juin 2026

  Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative condition whose osseous changes are often subtle on cone-beam CT (CBCT), making automated detection challenging. We study how well the DINO family of self-supervised vision transformers -- DINOv1, DINOv2, DINOv2+reg, and RAD…

• 3D Oral Modelling with Improved Vertex Distribution Using Matching-Based Learning

  Jihun Cho, Soo-Yeon Jeong, Eun-Jeong Bae, Sun-Young Ihm · 9 juin 2026

  In our previous work, a deep learning-based framework for 3D intraoral reconstruction was proposed. The model directly predicts explicit 3D point cloud coordinates from ten fixed-angle intraoral images, employing MobileNetV2 and Multi-head Attention for multi-view feature fusion, with a combined L1 …

• Deep Learning-based 3D Oral Cavity Reconstruction Using 2D Intraoral Images

  Jihun Cho, Soo-Yeon Jeong, Eun-Jeong Bae, Sun-Young Ihm · 5 juin 2026

  Oral 3D modelling is one of the most essential stages in dentistry, and many different approaches, such as impression taking and intraoral scanning, are commonly used for this phase, each with notable limitations. Impression taking, which involves placing alginate or silicone material in a tray and …

• Pocket-Dentist: On-Device Dental Image Understanding via Efficient Multimodal Large Language Models

  Kai Bian, Xucheng Guo, Bin Chen, Lingyan Ruan, Yiran Shen, Ting Dang, Hong Jia · 29 mai 2026

  Evaluations of dental vision-language models remain fragmented across datasets, task definitions and metrics, and often ignore their computational cost. This limits their widespread deployment for dental screening outside specialist centres, where timely inference, limited hardware, and local handli…

• HyDAR-Pano3D: A Hybrid Disentangled Anatomical Recovery Framework for Panoramic-to-3D Reconstruction

  Yaoyao Yue, Jérôme Schmid, Xiaoshuang Li, Eduardo Delamare, Jinman Kim · 21 mai 2026

  Panoramic radiograph (PR) is fundamentally used in routine dental care, but it inherently provides only a two-dimensional (2D) projection of complex three-dimensional (3D) craniofacial anatomy. Most existing learning-based methods attempt to computationally recover this 3D information by directly re…

• ImplantMamba: Long-range Sequential Modeling Mamba For Dental Implant Position Prediction

  Xinquan Yang, Congmin Wang, Xuguang Li, Yulei Li, Linlin Shen, Yongqiang Deng He Meng · 11 mai 2026

  In the design of surgical guides for implant placement, determining the precise implant position is a critical step. However, the implant region itself is often characterized by a lack of distinctive texture in medical images. Consequently, artificial intelligence (AI) models must infer the correct …

• Tracing Like a Clinician: Anatomy-Guided Spatial Priors for Cephalometric Landmark Detection

  Sidhartha Mohapatra, Pallavi Mohanty · 6 mai 2026

  Clinicians trace cephalometric radiographs following a structured anatomical workflow, yet no prior system encodes this into computation. We present a five-phase anatomy-guided pipeline producing confidence-weighted spatial priors that shape HRNet-W32 training, achieving 1.04 mm mean radial error on…

• Profile-Specific 3DMM Regression from a Single Lateral Face Image

  Taiki Kanaya, Hideo Saito · 5 mai 2026

  Single-image 3D face reconstruction is a core problem in computer vision, with important clinical applications such as cephalometric landmark analysis in orthodontics. Traditionally, this analysis relies on lateral X-ray imaging; however, frequent X-ray exposure is impractical due to radiation conce…

• Adaptive Texture-aware Masking for Self-Supervised Learning in 3D Dental CBCT Analysis

  Xinquan Yang, Jianfeng Ren, Xuguang Li, Kian Ming Lim, He Meng, Linlin Shen, Yongqiang Deng · 5 mai 2026

  Cone Beam Computed Tomography (CBCT) is pivotal for 3D diagnostic imaging in dentistry. However, the development of robust AI models for volumetric analysis is often constrained by the scarcity of large, annotated datasets. Self-supervised learning (SSL), particularly Masked Image Modeling (MIM), of…