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RadGenome/PMC-VQA

PMC-VQA Dataset PMC-VQA Dataset Daraset Structure Sample Dataset Structure PMC-VQA (version-1: 227k VQA pairs of 149k images). train.csv: metafile of train set test.csv: metafile of test set test_clean.csv: metafile of test clean set images.zip: images folder (update version-2: noncompound images). train2.csv: metafile of train set test2.csv: metafile of test set images2.zip: images folder Sample A row in train.csv is shown bellow… See the full description on the dataset page: https://huggingface.co/datasets/RadGenome/PMC-VQA.

sourceHugging Faceupdated 2y agoView on Hugging Face
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Dataset Card

PMC-VQA Dataset

Dataset Structure

PMC-VQA (version-1: 227k VQA pairs of 149k images).

  • train.csv: metafile of train set
  • test.csv: metafile of test set
  • test_clean.csv: metafile of test clean set
  • images.zip: images folder
  • (update version-2: noncompound images).
  • train2.csv: metafile of train set
  • test2.csv: metafile of test set
  • images2.zip: images folder

Sample

A row in train.csv is shown bellow,

Figure_pathPMC1064097_F1.jpg
QuestionWhat is the uptake pattern in the breast?
AnswerFocal uptake pattern
Choice AA:Diffuse uptake pattern
Choice BB:Focal uptake pattern
Choice CC:No uptake pattern
Choice DD:Cannot determine from the information given
Answer_labelB

Explanation to each key

  • Figure_path: path to the image
  • Question: question corresponding to the image
  • Answer: the correct answer corresponding to the image
  • Choice A: the provide choice A
  • Choice B: the provide choice B
  • Choice C: the provide choice C
  • Choice D: the provide choice D
  • Anwser_label: the correct answer label

Dataset License

The papers used for developing PMC-VQA are from the 'Commercial Use Allowed' split of the PMC Open Access Subset. We provide the detailed PubMed Central ID for each paper and corresponding licenses in the supplementary files, which are all under CC0 or CC BY licenses. Our final dataset, PMC-VQA, is under CC BY-SA licenses so that it can be widely used to support the development of medical generative-based VQA models.