A Multi-center Dental Panoramic Radiography Image Dataset for Impacted Teeth, Periodontitis, and Dental Caries: Benchmarking Segmentation and Classification Tasks.

Panoramic radiography imaging plays a crucial role in the diagnostic process of dental diseases. However, current artificial intelligence research datasets for panoramic radiography dental image processing are often limited to single-center and single-task scenarios, making it difficult to generaliz...

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Publicado en:Journal of Digital Imaging Vol. 37; no. 2; pp. 831 - 842
Autores principales: Li, Xiang, Ma, Xuan, Zhao, Yibai, Hu, Jingjing, Liu, Jie, Yang, Zhicheng, Han, Fangkai, Zhang, Jie, Liu, Weifan, Zhou, Zhongwei
Formato: diagnostic images pictorial research tables/charts Journal Article
Publicado: Springer Nature Apr2024
Acceso en línea:Ver este registro en EBSCOhost
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        atl: A Multi-center Dental Panoramic Radiography Image Dataset for Impacted Teeth, Periodontitis, and Dental Caries: Benchmarking Segmentation and Classification Tasks.
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          Li, Xiang
          Ma, Xuan
          Zhao, Yibai
          Hu, Jingjing
          Liu, Jie
          Yang, Zhicheng
          Han, Fangkai
          Zhang, Jie
          Liu, Weifan
          Zhou, Zhongwei
        affil: https://ror.org/02h8a1848 Department of Oral and Maxillofacial Surgery, General Hospital of Ningxia Medical University, 750004, Yinchuan, Ningxia, China
      sug:
        subj:
          Radiography, Panoramic
          Tooth, Impacted Radiography
          Periodontitis Radiography
          Dental Caries Radiography
          Benchmarking
          Algorithms
          Image Processing, Computer Assisted Methods
          Artificial Intelligence
          Human
          Retrospective Design
          Record Review
          Multicenter Studies
          Tomography, X-Ray Computed Methods
          Tooth Diseases Classification
          Funding Source
      ab: Panoramic radiography imaging plays a crucial role in the diagnostic process of dental diseases. However, current artificial intelligence research datasets for panoramic radiography dental image processing are often limited to single-center and single-task scenarios, making it difficult to generalize their results. To address this, we present a multi-center, multi-task labeled dataset. In this study, our dataset comprises three datasets obtained from different hospitals. The first set has 4940 panoramic radiography images and corresponding labels from the Stemmatological Hospital of the General Hospital of Ningxia Medical University. The second set includes 716 panoramic radiography images and labels from the People's Hospital of Yinchuan City, Ningxia. The third dataset contains 880 panoramic radiography images and labels from a hospital in Shenzhen, Guangdong Province. This comprehensive dataset encompasses three types of dental diseases: impacted teeth, periodontitis, and dental caries. Specifically, it comprises 2555 images related to impacted teeth, 2735 images related to periodontitis, and 1246 images related to dental caries. In order to evaluate the performance of the dataset, we conducted benchmark tests for segmentation and classification tasks on our dataset. The results show that the presented dataset could be effectively used for benchmarking segmentation and classification tasks critical to the diagnosis of dental diseases. To request our multi-center dataset, please visit the address: https://github.com/qinxin99/qinxini.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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