Dataset Name: LitMedImage – literature-derived Medical vs. Non-Medical Image Dataset ------------------- Description: ------------------- LitMedImage is a curated dataset of biomedical literature figures labeled as MEDICAL or NON-MEDICAL. The dataset is built from images extracted from PubMed Central Open Access (PMC-OA) articles and includes corresponding captions and parsed image metadata. Labels were generated using a large language model (LLM) following strict imaging definitions. This dataset is intended for research in figure classification, document parsing, and biomedical vision-language models. Columns: PMCID: PubMed Central article identifier (e.g., PMC1234567) Image_num: Index of the image within the article Online_file_path: Direct file path to the image under https://ftp.ncbi.nlm.nih.gov/pub/pmc/ Image_info_Cleaned: Parsed metadata describing the image contents Caption_Clean: Cleaned image caption from the original publication label: Binary classification label ("yes" for MEDICAL images, "no" for NON-MEDICAL images) ------------------- Label Definitions: ------------------- Label = "yes" (MEDICAL) Images that belong to clinical or biomedical imaging modalities, including: Radiology, Echocardiography, Dermoscopy, Histopathology, X-ray (Radiography), CT, MRI, Ultrasound, Nuclear Medicine (PET, SPECT, PET-CT, PET-MRI), Optical Imaging, Thermography, Elastography, Mammography, Digital Breast Tomosynthesis, Fluoroscopy, Clinical Imaging Label = "no" (NON-MEDICAL) Images that are statistical plots or schematic illustrations, including: Bar charts, Histograms, Line graphs, Scatter or Bubble plots, Pie or Donut charts, Area charts, Heatmaps, Box or Violin plots, Radar or Spider charts, Treemaps, Network graphs, Drawings, Conceptual diagrams ------------------- Task Instruction: ------------------- Given an image, classify whether it is a MEDICAL image or a NON-MEDICAL image. Data Source: All images originate from the PubMed Central Open Access Subset via the public FTP archive at: https://ftp.ncbi.nlm.nih.gov/pub/pmc/ Intended Use: - Binary image classification (medical vs. non-medical) - Multimodal image + caption classification - Figure filtering for automated document processing - Pre-filtering figures for vision-language model training or inference Citation: [To be added]