PETWB-REP: A Multi-Cancer Whole-Body FDG PET/CT and Radiology Report Dataset for Medical Imaging Research

Le Xue, Gang Feng, Wenbo Zhang, Yichi Zhang, Lanlan Li +4 more
11/5/2025
cs.CV

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Abstract

Publicly available, large-scale medical imaging datasets are crucial for developing and validating artificial intelligence models and conducting retrospective clinical research. However, datasets that combine functional and anatomical imaging with detailed clinical reports across multiple cancer types remain scarce. Here, we present PETWB-REP, a curated dataset comprising whole-body 18F-Fluorodeoxyglucose (FDG) Positron Emission Tomography/Computed Tomography (PET/CT) scans and corresponding radiology reports from 490 patients diagnosed with various malignancies. The dataset primarily includes common cancers such as lung cancer, liver cancer, breast cancer, prostate cancer, and ovarian cancer. This dataset includes paired PET and CT images, de-identified textual reports, and structured clinical metadata. It is designed to support research in medical imaging, radiomics, artificial intelligence, and multi-modal learning.

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Cite this paper

@article{xue2025petwbrep,
  title  = {PETWB-REP: A Multi-Cancer Whole-Body FDG PET/CT and Radiology Report Dataset for Medical Imaging Research},
  author = {Le Xue and Gang Feng and Wenbo Zhang and Yichi Zhang and Lanlan Li and Shuqi Wang and Liling Peng and Sisi Peng and Xin Gao},
  year   = {2025},
  eprint = {2511.03194},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2511.03194v1}
}

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