ArticleData in brief2025
Incisor pulp chamber tomographic image dataset for dental age estimation.
Article in Data in brief, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Multi-view deep fusion for forensic dental age estimation in tomographic imaging.International journal of legal medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate tooth detection, segmentation, and age estimation are critical tasks in forensic odontology, helping to identify undocumented individuals in immigration cases, unidentified persons, and in the analysis of corpses and body fragments in accidents. This dataset was assembled to support such applications, comprising images of the upper central incisors from a diverse cohort of Brazilian individuals aged 18 to 60 from the Zona da Mata Mineira, obtained using standardized Cone Beam Computed Tomography (CBCT) scanning protocols. Each scan includes both coronal and sagittal views, providing a comprehensive coverage of the tooth structure. The dataset includes bounding box annotations for precise tooth localization. Additionally, the tooth crown and pulp chamber are essential for age estimation, as the crown's enamel protects the dentin, and the dimensions of the pulp chamber decrease over time due to secondary dentin deposition. Therefore, segmentation annotations are provided for both the crown and pulp chamber to capture these critical structural details. Each image is also labeled with detailed metadata, including age, sex, and tooth number, to support a wide range of research approaches and objectives, maximizing the dataset's utility and making sure it provides comprehensive information for various analytical needs. In addition, the patient code is present in the images, serving as an identifier. This dataset is a valuable resource for researchers aiming to develop and validate machine learning models for various dental applications. Its versatility supports a wide range of tasks, from automated dental diagnostics to advanced forensic investigations, making it a significant contribution to the field of dental image analysis.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.