Evidence map›Paper›PMID 38321312›Full record

ArticleJournal of imaging informatics in medicine2024

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

Xiang Li, Xuan Ma, Yibai Zhao, Jingjing Hu, Jie Liu, Zhicheng Yang, Fangkai Han, Jie Zhang, Weifan Liu, Zhongwei Zhou

Open access · greenAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of imaging informatics in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 9 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 7 institutions in 1 country.

Xiang LiDepartment of Oral and Maxillofacial Surgery, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China.
Xuan MaThe School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China.
Yibai ZhaoThe School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China.
Jingjing HuDepartment of Oral and Maxillofacial Surgery, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China.
Jie LiuThe School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China. jieliu@bjtu.edu.cn.
Zhicheng YangDepartment of Oral and Maxillofacial Surgery, Shanghai Stomatological Hospital and School of Stomatology, Fudan University, Shanghai, 200001, China.
Fangkai HanShanghai Stomatological Hospital, Fudan University, Shanghai, 200001, China.
Jie ZhangSchool of Chips, Xi'an Jiaotong-Liverpool University, Suzhou, Jiangsu, China. Jie.Zhang06@xjtlu.edu.cn.
Weifan LiuCollege of Science, Beijing Forestry University, Beijing, 100083, China.
Zhongwei ZhouDepartment of Oral and Maxillofacial Surgery, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China. zzwjoel@hotmail.com.
Beijing Jiaotong University · CNShanghai Stomatological Hospital · CNAnhui University of Science and Technology · CNBeijing Forestry University · CNFudan University · CNNingxia Medical University · CNXi’an Jiaotong-Liverpool University · CN

Funding

Innovative Research Group Project of the National Natural Science Foundation of China 81571836Innovative Research Group Project of the National Natural Science Foundation of China KKA309004533Key Research and Development Program of Ningxia 2023BEG02036
6 · The paper itself

Abstract

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 .

Indexed as

Dental CariesImage Processing, Computer-AssistedPeriodontitisRadiography, PanoramicTooth, ImpactedBenchmarkingHumansDatasetDental cariesDental imageImpacted teethPanoramic radiography imagePeriodontitis

Identifiers

PMID38321312
PMCPMC11031544
OpenAlexW4391563177

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.