ArticleInternational journal of legal medicine2021
Age estimation based on 3D pulp chamber segmentation of first molars from cone-beam-computed tomography by integrated deep learning and level set.
Article in International journal of legal medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.
- A systematic overview of dental methods for age assessment in living individuals: from traditional to artificial intelligence-based approaches.International journal of legal medicine · 2023Pooled it
- Multi-view deep fusion for forensic dental age estimation in tomographic imaging.International journal of legal medicine · 2026Article
- Dental Age-Group Classification from Panoramic Radiographs Using Convolutional Neural Networks.Diagnostics (Basel, Switzerland) · 2026Article
- Deep learning-based method for estimating age from periapical radiographs of upper incisors in a Thai population.Imaging science in dentistry · 2025Article
- Accuracy and challenges in age estimation in adults: a scoping review of anthropological, dental, biochemical, and molecular methods.Forensic science, medicine, and pathology · 2025Article
- A fully automated deep learning framework for age estimation in adults using periapical radiographs of canine teeth.International journal of legal medicine · 2025Article
- Incisor pulp chamber tomographic image dataset for dental age estimation.Data in brief · 2025Article
- Assessment of volumetric changes after regenerative endodontic procedures using semiautomated and 3D U-NET automated CBCT segmentation: a retrospective cohort study.BMC oral health · 2025Article
- Comparative Age Estimation Using 2D and 3D Imaging of Maxillary and Mandibular Molars: A Prospective Study.Cureus · 2025Article
- Age estimation by volumetric analysis of teeth using cone beam computed tomography.Oral radiology · 2024Article
- Performance of Artificial Intelligence Models Designed for Automated Estimation of Age Using Dento-Maxillofacial Radiographs-A Systematic Review.Diagnostics (Basel, Switzerland) · 2024Review
- Cone-Beam Computed Tomography for the Evaluation of Dental Pulp Chamber Volume: Implications for Clinics and Teaching.Dentistry journal · 2024Article
- Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.Dento maxillo facial radiology · 2024Article
- Performance of artificial intelligence using cone-beam computed tomography for segmentation of oral and maxillofacial structures: A systematic review and meta-analysis.Journal of clinical and experimental dentistry · 2023Review
- Age estimation based on 3D pulp segmentation of first molars from CBCT images using U-Net.Dento maxillo facial radiology · 2023Article
- Semi-supervised automatic dental age and sex estimation using a hybrid transformer model.International journal of legal medicine · 2023Article
- Validation of data mining models by comparing with conventional methods for dental age estimation in Korean juveniles and young adults.Scientific reports · 2023Article
- Age Estimation Using Maxillary Central Incisor Analysis on Cone Beam Computed Tomography Human Images.International journal of environmental research and public health · 2022Article
- Population-specific age estimation in Black Americans and Chinese people based on pulp chamber volume of first molars from cone beam computed tomography.International journal of legal medicine · 2022Article
- With or without human interference for precise age estimation based on machine learning?International journal of legal medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesTo develop an automatic segmentation method to segment the pulp chamber of first molars from 3D cone-beam-computed tomography (CBCT) images, and to estimate ages by calculated pulp volumes. MATERIALS AND
methodsPatients with CBCT scans were retrospectively identified. The age estimation was formulated as CBCT image segmentation using a coarse-to-fine strategy by integrated deep learning (DL) and level set (LS), followed by establishing a linear regression model. On the training data, DL model was trained for coarse segmentation. The validation set was to determine the optimal DL model, and a LS method established on it was to refine the coarse segmentation. On the testing data, the integrated DL and LS method was applied for pulp chamber segmentation, followed by volume calculation and age estimation. Statistical analysis was performed by Wilcoxon rank sum test to demonstrate gender difference in pulp chamber volume, and volume difference between maxillary and mandibular molars. Wilcoxon signed-rank test was adopted to compare true and estimated ages.
resultsA total of 180 CBCT studies were randomly divided into 37/10/133 patients for training, validation, and testing data, respectively. In the training and validation sets, the results showed high spatial overlaps between manual and automatic segmentation (dice = 87.8%). For the testing set, the estimated human ages were not significantly different with true human age (p = 0.57), with a correlation coefficient r = 0.74.
conclusionsAn integrated DL and LS method was able to segment pulp chamber of first molars from 3D CBCT images, and the derived pulp chamber volumes could effectively estimate the human ages.
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.