ArticleScientific data2025
A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Augmenting medical image specific foundation model with classical radiomic signatures for improved nasopharyngeal carcinoma stage classification.Frontiers in medical technology · 2026Article
- A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation.Scientific data · 2025Article
- MFNet: Meta-learning based on frequency-space mix for MRI segmentation in nasopharyngeal carcinoma.Journal of cellular and molecular medicine · 2024Article
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Authors and funding
13 authors.
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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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