ArticleDento maxillo facial radiology2019
Software comparison to analyze bone radiomics from high resolution CBCT scans of mandibular condyles.
Article in Dento maxillo facial radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Radiomics-Based Diagnosis in Dentomaxillofacial Radiology: A Systematic Review.Journal of imaging informatics in medicine · 2025Pooled it
- Diagnosis of temporomandibular disorders using artificial intelligence technologies: A systematic review and meta-analysis.PloS one · 2022Pooled it
- Quantitative Imaging of the Mandibular Condyle: Radiomics and Microarchitectural Biomarkers.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2026Review
- Multimodal Radiogenomic Imaging in Oropharyngeal Squamous Cell Carcinoma: Implications for Dentomaxillofacial Radiology.Medical sciences (Basel, Switzerland) · 2026Review
- Observational
- Radiomic Parameters in Periapical Lesions: A CBCT Analysis Evaluating Volumetric Size, Cortical Expansion, Erosion, and Shape.European endodontic journal · 2024Article
- A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Neuroimaging and artificial intelligence for assessment of chronic painful temporomandibular disorders-a comprehensive review.International journal of oral science · 2023Review
- Current Applications of Deep Learning and Radiomics on CT and CBCT for Maxillofacial Diseases.Diagnostics (Basel, Switzerland) · 2022Review
- Predicting Osteoarthritis of the Temporomandibular Joint Using Random Forest with Privileged Information.Ethical and philosophical issues in medical imaging, multimodal learning and fusion across scales for clinical decision support, and topological data analysis for biomedical imaging : 1st International Workshop, EPIMI 2022, 12th Interna... · 2022Article
- Quantitative bone imaging biomarkers and joint space analysis of the articular Fossa in temporomandibular joint osteoarthritis using artificial intelligence models.Frontiers in dental medicine · 2022Article
- Temporomandibular Joint Osteoarthritis Diagnosis Using Privileged Learning of Protein Markers.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- Benchmarking Various Radiomic Toolkit Features While Applying the Image Biomarker Standardization Initiative toward Clinical Translation of Radiomic Analysis.Journal of digital imaging · 2021Article
- Decision Support Systems in Temporomandibular Joint Osteoarthritis: A review of Data Science and Artificial Intelligence Applications.Seminars in orthodontics · 2021Article
- Development and Validation of a Magnetic Resonance Imaging-Based Machine Learning Model for TMJ Pathologies.BioMed research international · 2021Article
- Radiomics: from qualitative to quantitative imaging.The British journal of radiology · 2020Review
- Evaluation and Correlation of Condylar Cortication by Cone-Beam Computed Tomography: A Retrospective Study.Contemporary clinical dentistryArticle
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectivesRadiomics refers to the extraction and analysis of advanced quantitative imaging from medical images to diagnose and/or predict diseases. In the dentistry field, the bone data from mandibular condyles could be computationally analyzed using the voxel information provided by high-resolution CBCT scans to increase the diagnostic power of temporomandibular joint (TMJ) conditions. However, such quantitative information demands innovative computational software, algorithm implementation, and validation. Our study's aim was to compare a newly developed BoneTexture application to two-consolidated software with previous applications in the medical field, Ibex and BoneJ, to extract bone morphometric and textural features from mandibular condyles.
methodsWe used an imaging database of HR-CBCT TMJs scans with an isotropic voxel size of 0.08 mm
resultsThe results showed a high Spearman correlation among the software applications (
conclusionsOur data showed consistency among the three applications to analyze bone radiomics in high-resolution CBCT. Further studies are necessary to evaluate the applicability of those variables as new bone imaging biomarkers to diagnose bone diseases affecting TMJs.
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