  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.
