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Data in brief · 2025

Incisor pulp chamber tomographic image dataset for dental age estimation.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Pereira Davi Magalhães, Pacelli Alexandre Vieira Pereira, Lopes Junior William José, Villela Saulo Moraes, Bernardino Heder Soares, Vieira Marcelo Bernardes, Devito Karina Lopes

Аннотация

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.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

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