A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866909728613859328 |
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| author | Li, Yin Chen, Qi Wang, Kai Li, Meige Si, Liping Guo, Yingwei Xiong, Yu Wang, Qixing Qin, Yang Xu, Ling van der Smagt, Patrick Tang, Jun Chen, Nutan |
| author_facet | Li, Yin Chen, Qi Wang, Kai Li, Meige Si, Liping Guo, Yingwei Xiong, Yu Wang, Qixing Qin, Yang Xu, Ling van der Smagt, Patrick Tang, Jun Chen, Nutan |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_03253 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation Li, Yin Chen, Qi Wang, Kai Li, Meige Si, Liping Guo, Yingwei Xiong, Yu Wang, Qixing Qin, Yang Xu, Ling van der Smagt, Patrick Tang, Jun Chen, Nutan Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning 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. |
| title | A dataset of primary nasopharyngeal carcinoma MRI with multi-modalities segmentation |
| topic | Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2404.03253 |