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Open research questions in Dental Radiography and Imaging

350 unresolved questions extracted from the limitations and future-work sections of 2,484 Dental Radiography and Imaging papers in our library. Each links back to the study that raised it.

What the literature leaves open

  • Anatomical variability and limited residual bone height pose challenges for implant placement. Maxillary sinus pneumatization influences the selection of appropriate implant dimensions. Overfitting and limited training data pose challenges for deep learning models.

    Multi-output classification of dental implant placement parameters in the posterior maxilla from CBCT images using a two-stage vision transformer framework · 2026 · DOI

  • Further evaluation of the ViT model on larger and more diverse datasets to assess its generalizability - Investigation of the model's performance in real-world clinical settings and its potential impact on patient outcomes - Exploration of the application of the ViT model to other medical imaging tasks and domains

    Multi-output classification of dental implant placement parameters in the posterior maxilla from CBCT images using a two-stage vision transformer framework · 2026 · DOI

  • The lack of automated detection of the articular eminence slope and fossa boundaries in Meshmixer. The need for manual definition of the Frankfort plane and creation of sagittal reformats through the condylar head. The challenge of ensuring accurate and reproducible results in a freeware environment.

    Creation of a semi-adjustable virtual articulator by integrating intraoral, facial, and cone-beam computed tomography scans in freeware software: A proof of concept · 2026 · DOI

  • The proof of concept does not replace certified clinical solutions, - A facial scan geometry is expression-dependent, - No constraints from the glenoid fossa or articular eminence are enforced by the software, - Trajectories are user-driven via the measured parameters and pivot geometry, - The study lacks validation against commercial systems and conventional clinical records

    Creation of a semi-adjustable virtual articulator by integrating intraoral, facial, and cone-beam computed tomography scans in freeware software: A proof of concept · 2026 · DOI

  • The choice between a palatal bar and a palatal strap often reflects the personal preferences of dentists - A model for predicting whether the maxillary major connector type was an anterior-posterior bar was not constructed because of the insufficient sample size - The application of AI in RPD design remains relatively limited

    Explainable artificial intelligence system using a convolutional neural network for designing major connectors of removable partial denture framework · 2026 · DOI

  • Further research is needed to improve the accuracy and robustness of the AI-based system - The development of more advanced AI models that can handle complex cases and variability in clinical skills and experience - The integration of the AI-based system with other dental technologies to enhance its practical applications

    Explainable artificial intelligence system using a convolutional neural network for designing major connectors of removable partial denture framework · 2026 · DOI

  • data-driven development approaches that backcast the desired clinical performance - integration of multi-layered data encompassing nanoscale structures, biological responses, occlusal mechanics, and clinical outcomes

    Prosthodontic research in the big data era · 2026 · DOI

  • The gap between basic science and clinical application is a fundamental barrier to the successful translation of novel biomaterials into clinical practice. Current prosthodontic research remains compartmentalized, with clinical, biological, and material sciences progressing within their own independent frameworks.

    Prosthodontic research in the big data era · 2026 · DOI

  • The study does not provide a comprehensive description of the factors that influence registration or the systematic approaches for its improvement. The study does not address inherent errors in the registration process. The study has a limited number of participants and registrations.

    Exploration of predominant error sources in intraoral scanning and cone-beam computed tomography semiautomated registration · 2026 · DOI

  • Studies on the registration of CBCT images and IOSs should provide comprehensive descriptions of the factors that influence registration or the systematic approaches for its improvement. Research on inherent errors in the registration process is needed. Further studies with larger sample sizes are required to confirm the findings.

    Exploration of predominant error sources in intraoral scanning and cone-beam computed tomography semiautomated registration · 2026 · DOI

  • Due to limited data in Iranian populations, this study assessed the radiographic density of normal periapical bone using panoramic imaging.

    Radiographic Assessment of Normal Periapical Bone Density: A Descriptive Analysis Based on Digital Imaging · 2026 · DOI

  • Abstract Objectives This review examines how contemporary artificial intelligence (AI) systems primarily convolutional and artificial neural networks support diagnosis and decision-making across core endodontic imaging tasks, and synthesizes where these tools add clinical value, where evidence is limited, and what is needed for responsible integration into practice.

    Current evidence on deep learning diagnostic accuracy and clinician augmentation in endodontic imaging tasks · 2026 · DOI

  • Conclusions: The evidence is sparse and methodologically heterogeneous and does not support firm conclusions regarding clinical effectiveness.

    Vitamins in the Management of Inferior Alveolar Nerve Sensory Disturbances: A Scoping Review of Randomized Studies · 2026 · DOI

  • OBJECTIVES: The necessity of a second molar region implant for Kennedy Class II classification of unilateral partially edentulous arches remains controversial.

    Function, Quality of Life, and Food Intake in Patients Without Second Molar Implants: A Prospective Cohort Study · 2025 · DOI

  • Cliniface is readily available open-access software for automatic facial landmarking, its validity has not been fully investigated.

    The accuracy of automated facial landmarking - a comparative study between Cliniface software and patch-based Convoluted Neural Network algorithm · 2025 · DOI

  • CONCLUSION: While the AI-based platform shows promise in detecting impacted third molars, it is still insufficient to replace human evaluation as the standard for assessing impacted teeth in panoramic radiographs.

    Assessment of AI software's diagnostic accuracy in identifying impacted teeth in panoramic radiographs · 2025 · DOI

  • CONCLUSIONS: AI and advanced imaging techniques are promising for periodontal screening, diagnosis and prognosis in the dental setting, although the evidence remains inconsistent and inconclusive.

    Emerging Applications of Digital Technologies for Periodontal Screening, Diagnosis and Prognosis in the Dental Setting · 2025 · DOI

  • Despite recent applications of artificial intelligence (AI) in tooth segmentation, its performance in mandibular third molar segmentation remains underexplored.

    Artificial intelligence-enabled automatic segmentation of impacted mandibular third molars: A comprehensive comparison of multiple algorithms · 2025 · DOI

  • However, its quantitative accuracy in representing true enamel–dentin (E–D) and dentin–pulp (D–P) distances remains uncertain.

    Quantitative comparison of enamel–dentin and dentin–pulp distances between cone-beam computed tomography and histological sections: An ex vivo study · 2025 · DOI

  • BACKGROUND: Cone Beam Computed Tomography (CBCT) plays a critical role in oral and maxillofacial surgery (OMFS), yet the training needs of residents regarding CBCT viewer interfaces remain underexplored.

    Assessing oral surgery residents’ competencies and training needs in tomography interfaces through a usability framework · 2025 · DOI

  • Future research should focus on the long-term impact of usability-driven training on clinical performance and patient outcomes.

    Assessing oral surgery residents’ competencies and training needs in tomography interfaces through a usability framework · 2025 · DOI

  • The findings suggest that more specific imaging protocols may improve safety and clinical outcomes, and that further investigation of long-term outcomes may provide valuable insights.

    A global overview of the use of cone beam computed tomography in dentistry: a bibliometric review focusing on paediatric patients · 2025 · DOI

  • Future research can focus on improving the accuracy and efficiency of automated tooth detection and numbering. Future research can explore the application of deep learning models to other tasks in dentistry.

    Teeth identification and numbering in mixed dentition: evaluating deep learning models for pediatric panoramic radiographs · 2026 · DOI

  • The study identifies a gap in the use of automated tooth detection and numbering in pediatric panoramic radiographs. The gap is due to the limitations of traditional methods and the need for more accurate and efficient solutions.

    Teeth identification and numbering in mixed dentition: evaluating deep learning models for pediatric panoramic radiographs · 2026 · DOI

  • Additional preoperative preparation is required, which can be time-consuming. Guided surgery also has limitations, including the need for a trephine bur and a surgical guide.

    Guided endodontic microsurgery using a simplified surgical guide for mandibular first molars with intact buccal cortical bone · 2026 · DOI

Most-cited papers in Dental Radiography and Imaging

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350 open questions have been extracted from the limitations and future-work passages of 2,484 Dental Radiography and Imaging papers in our library. Each one below links back to the study that raised it, so you can read the original claim in context.

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