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

Fuente: arXiv
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Autores principales: 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
Formato: Preprint
Publicado: 2024
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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