牙源性病变CBCT与组织病理综合数据集

资源简介

牙源性病变CBCT与组织病理综合数据集

【数据集背景】

本数据集源站标题为《Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms》。配套论文《Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms》发表于 Scientific Data（2026），DOI：10.1038/s41597-026-07112-7。源站首次发布：2026-05-20。

【数据内容】

源站原始描述：The Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset (DOLCHID) is the first publicly available paired resource that combines radiological and pathological data for odontogenic lesion research. It comprises 262 patient cases, each including a pre-operative cone-beam computed tomography (CBCT) scan with expert-verified segmentation masks and a corresponding post-operative haematoxylin and eosin (H&E)-stained histopathology slide with annotated regions of interest. The dataset c…

【数据结构与技术规格】

文件数 1 个，合计 42.59 GB。数据集 DOI：10.6084/m9.figshare.30156622.v1。

【主题与分类】

源站学科分类：Computer Vision。主题标签：CBCT image、Histopathologic image、Dental disease、deep learning。

【适用方向】

多模态数据适合跨模态对齐、融合建模与联合表征学习方向的研究。

【获取与许可】

源站页面：https://springernature.figshare.com/articles/dataset/Dental_Odontogenic_Lesion_CBCT_and_Histopathology_Integrated_Dataset_for_Benchmarking_Deep_Learning_Algorithms/30156622

使用许可：CC BY（https://creativecommons.org/licenses/by/4.0/）。

规范引用：Kim, Jinman; Huang, Zimo; Xia, Tian; Huang, Shengfu; Bi, Lei; Wu, Tianfu; et al. (2026). Dental Odontogenic Lesion CBCT and Histopathology Integrated Dataset for Benchmarking Deep Learning Algorithms. figshare. Dataset