TBI Image/Text (TBI-IT): Comprehensive Text and Image Datasets for Traumatic Brain Injury Research

Jie Li; Jiaying Wen; Tongxin Yang; Fenglin Cai; Miao Wei; Zhiwei Zhang; Li Jiang

TBI Image/Text (TBI-IT): Comprehensive Text and Image Datasets for Traumatic Brain Injury Research

Image and Video Processing 2024-03-15 v1 Computer Vision and Pattern Recognition

Authors: Jie Li , Jiaying Wen , Tongxin Yang , Fenglin Cai , Miao Wei , Zhiwei Zhang , Li Jiang

Abstract

In this paper, we introduce a new dataset in the medical field of Traumatic Brain Injury (TBI), called TBI-IT, which includes both electronic medical records (EMRs) and head CT images. This dataset is designed to enhance the accuracy of artificial intelligence in the diagnosis and treatment of TBI. This dataset, built upon the foundation of standard text and image data, incorporates specific annotations within the EMRs, extracting key content from the text information, and categorizes the annotation content of imaging data into five types: brain midline, hematoma, left cerebral ventricle, right cerebral ventricle and fracture. TBI-IT aims to be a foundational dataset for feature learning in image segmentation tasks and named entity recognition.

Keywords

traumatic brain injury medical dataset electronic medical records head CT images image segmentation named entity recognition

Cite

@article{arxiv.2403.09062,
  title  = {TBI Image/Text (TBI-IT): Comprehensive Text and Image Datasets for Traumatic Brain Injury Research},
  author = {Jie Li and Jiaying Wen and Tongxin Yang and Fenglin Cai and Miao Wei and Zhiwei Zhang and Li Jiang},
  journal= {arXiv preprint arXiv:2403.09062},
  year   = {2024}
}

Comments

arXiv admin note: substantial text overlap with arXiv:2401.15934

TBI Image/Text (TBI-IT): Comprehensive Text and Image Datasets for Traumatic Brain Injury Research

Abstract

Keywords

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