A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation

Yin Li, Qi Chen, Kai Wang, Meige Li, Liping Si +8 more
4/4/2024
eess.IVcs.AIcs.CV

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Abstract

Multi-modality magnetic resonance imaging(MRI) data facilitate the early diagnosis, tumor segmentation, and disease staging in the management of nasopharyngeal carcinoma (NPC). The lack of publicly available, comprehensive datasets limits advancements in diagnosis, treatment planning, and the development of machine learning algorithms for NPC. Addressing this critical need, we introduce the first comprehensive NPC MRI dataset, encompassing MR axial imaging of 277 primary NPC patients. This dataset includes T1-weighted, T2-weighted, and contrast-enhanced T1-weighted sequences, totaling 831 scans. In addition to the corresponding clinical data, manually annotated and labeled segmentations by experienced radiologists offer high-quality data resources from untreated primary NPC.

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Cite this paper

@article{li2024dataset,
  title  = {A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation},
  author = {Yin Li and Qi Chen and Kai Wang and Meige Li and Liping Si and Yingwei Guo and Yu Xiong and Qixing Wang and Yang Qin and Ling Xu and Patrick van der Smagt and Jun Tang and Nutan Chen},
  year   = {2024},
  eprint = {2404.03253},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2404.03253v3}
}

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