Lesion_Dataset: Periapical Radiographs for Lesion Classification
收藏Zenodo2026-03-01 更新2026-05-26 收录
下载链接：
https://zenodo.org/doi/10.5281/zenodo.18824282
下载链接
链接失效反馈官方服务：
资源简介：
Lesion_Dataset is a collection of grayscale periapical radiographic images in TIFF (.TIF) format. Expert clinicians curated the images from routine dental examinations of 1,295 patients conducted at a dental clinic in Ankara, Türkiye, between 2006 and 2023. Each image corresponds to a distinct periapical view of a tooth root.
Labels: image-level binary labels based on expert visual assessment only (no pixel-wise annotations or segmentation masks).
Lesioned: 1,192 images
Healthy: 1,093 images
Total: 2,285 images
File naming convention: files are named as PXXXXXX_YYY.TIF. The prefix before the underscore denotes a pseudonymous patient identifier (e.g., P000824). Files sharing the same prefix belong to the same patient.
License: Creative Commons Attribution 4.0 International (CC BY 4.0).
Suggested citation: https://doi.org/10.5281/zenodo.18824283
Related publications (please cite if you use the dataset in academic work):
Can, Z., & Aydin, E. (2025). Explainable CNN–Radiomics Fusion and Ensemble Learning for Multimodal Lesion Classification in Dental Radiographs. Diagnostics, 15(16), 1997.
Can, Z., Isik, S., & Anagun, Y. (2024). CVApool: Using the null-space of CNN weights for tooth disease classification. Neural Computing and Applications, 36(26), 16567–16579.
Contact: zcan@ogu.edu.tr | https://web.ogu.edu.tr/zuhalcan/
提供机构：
Zenodo创建时间：
2026-03-01
