TBI Image/Text (TBI-IT): Comprehensive Text and Image Datasets for Traumatic Brain Injury Research
This dataset addresses the need for comprehensive data in medical AI for traumatic brain injury, but it is incremental as it builds on existing data types with new annotations.
The authors introduced TBI-IT, a new dataset combining electronic medical records and head CT images for traumatic brain injury research, designed to improve AI accuracy in diagnosis and treatment by including specific annotations for text and image data.
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.