Incisor pulp chamber tomographic image dataset for dental age estimation

Area of Science:

• Forensic Odontology
• Dental Image Analysis
• Medical Imaging

Background:

• Accurate tooth analysis is crucial for identifying individuals in forensic cases.
• Existing datasets may lack diversity or comprehensive annotations for advanced applications.

Purpose of the Study:

• To present a novel dataset of Cone Beam Computed Tomography (CBCT) scans of upper central incisors.
• To support research in tooth detection, segmentation, and age estimation using machine learning.

Main Methods:

• Acquired CBCT scans from a diverse cohort of 18-60 year old Brazilian individuals.
• Included coronal and sagittal views with bounding box and segmentation annotations for tooth crown and pulp chamber.
• Provided detailed metadata including age, sex, tooth number, and patient code.

Main Results:

• The dataset offers comprehensive imaging data with precise annotations.
• It facilitates the development and validation of machine learning models for dental applications.
• Enables detailed analysis of tooth structure relevant to age estimation.

Conclusions:

• This dataset is a valuable resource for advancing forensic odontology and dental image analysis.
• It supports automated diagnostics and complex forensic investigations.
• Promotes further research in machine learning applications within dentistry.