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Related Experiment Video

Updated: Aug 7, 2025

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
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Medical image captioning via generative pretrained transformers.

Alexander Selivanov1,2, Oleg Y Rogov1, Daniil Chesakov1,3

  • 1Skolkovo Institute of Science and Technology, Bolshoy blvd., 30/1, Moscow, 121205, Russia.

Scientific Reports
|March 14, 2023
PubMed
Summary

This study introduces an AI model for generating radiology reports by analyzing medical images and patient data. The model effectively describes pathologies and their locations, improving clinical image captioning.

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Area of Science:

  • Artificial Intelligence in Medicine
  • Medical Imaging Analysis
  • Natural Language Processing

Background:

  • Clinical image interpretation relies heavily on accurate and descriptive reports.
  • Generating these reports manually is time-consuming and prone to variability.
  • Integrating radiological scans with patient data can enhance diagnostic accuracy.

Purpose of the Study:

  • To develop an automated model for clinical image caption generation.
  • To combine radiological scan analysis with structured patient information.
  • To produce comprehensive radiology records with pathology localization.

Main Methods:

  • A novel model integrating Show-Attend-Tell and GPT-3 language models was proposed.
  • The model analyzes radiological scans and textual patient records.
  • 2D heatmaps were generated to localize identified pathologies.

Main Results:

  • The model successfully generated descriptive textual summaries of clinical images.
  • Pathology identification, location, and visual localization via heatmaps were achieved.
  • Effective applicability to chest X-ray image captioning was demonstrated on Open-I and MIMIC-CXR datasets.

Conclusions:

  • The proposed model offers an efficient approach to automatic radiology report generation.
  • Combining image and text analysis enhances the comprehensiveness of clinical captions.
  • This technology shows promise for improving medical documentation and diagnostic support.