Publication: The RSNA cervical spine fracture CT dataset
Program
KU-Authors
KU Authors
Co-Authors
Lin, Hui Ming
Colak, Errol
Richards, Tyler
Kitamura, Felipe C.
Prevedello, Luciano M.
Talbott, Jason
Ball, Robyn L.
Gumeler, Ekim
Yeom, Kristen W.
Hamghalam, Mohammad
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Abstract
This dataset is composed of cervical spine CT images with annotations related to fractures; it is available at https://www.kaggle.com/competitions/rsna-2022-cervical-spine-fracture-detection/. Key Points This is, to our knowledge, the largest publicly available adult cervical spine fracture CT dataset, with contributions from 12 institutions across nine countries and six continents. This dataset includes medical images, segmentations, and expert annotations from a large cohort of radiologists with subspecialist expertise in spine imaging. This dataset was used successfully for the Radiological Society of North America 2022 Cervical Spine Fracture Detection competition hosted on the Kaggle machine learning platform. The dataset is made freely available to the research community for noncommercial use.
Source
Publisher
Radiological Society of North America Inc.
Subject
Computer science, artificial intelligence, Radiology, nuclear medicine and medical imaging
Citation
Has Part
Source
Radiology: Artificial Intelligence
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Edition
DOI
10.1148/ryai.230034