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Related Experiment Video

Updated: Apr 12, 2026

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DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures.

Xu-Cheng Yin1, Chun Yang1, Wei-Yi Pei1

  • 1Department of Computer Science and Technology, School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.

Plos One
|May 8, 2015
PubMed
Summary

DeTEXT is a new, large-scale database for evaluating text extraction from biomedical figures. This resource aids in developing automated systems to mine crucial experimental evidence from scientific literature.

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Area of Science:

  • Biomedical Informatics
  • Computer Vision
  • Natural Language Processing

Background:

  • Biomedical literature contains millions of figures with vital experimental evidence.
  • Extracting text from these figures is crucial for information mining.
  • Automated systems require high-quality ground truth data for development.

Purpose of the Study:

  • To introduce DeTEXT, the first publicly available, human-annotated, large-scale dataset for evaluating text extraction from biomedical figures.
  • To provide a robust benchmark for developing and assessing automated figure-text extraction systems.

Main Methods:

  • Selection of 500 biomedical figures from 288 open-access full-text articles.
  • Development of annotation guidelines and tools for human annotators.
  • Annotation of 9308 text regions within the selected figures.
  • Analysis of inter-annotator agreement and annotation reliability.

Main Results:

  • Creation of DeTEXT, a comprehensive dataset comprising 288 articles, 500 figures, and 9308 annotated text regions.
  • Demonstration of high-quality, human-annotated data suitable for training and evaluating text extraction models.
  • Summary of dataset statistics and provision of evaluation protocols.

Conclusions:

  • DeTEXT serves as a valuable resource for advancing automated text extraction from biomedical figures.
  • Identified challenges and future research directions in figure-text detection and recognition were discussed.
  • The DeTEXT database is publicly accessible for research use.