A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 5 of its 32 references that are in the map. First posted on arXiv 4 Apr 2024.
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5 of 32 references.
References · 5
- 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
- 2017CNN-based Segmentation of Medical Imaging Datacited by 48
- 2022CDDSA: Contrastive Domain Disentanglement and Style Augmentation for Generalizable Medical Image Segmentationcited by 18
- 2018MMFNet: A Multi-modality MRI Fusion Network for Segmentation of Nasopharyngeal Carcinomacited by 8
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Citing papers per year: 2026: 2.
2 papers.