AI challenges

Artificial intelligence (AI) promises to provide tools that will enhance the efficiency and accuracy of radiologic diagnoses. RSNA organizes AI challenges to spur the creation of AI tools for radiology. 

To build these tools, AI researchers need access to substantial volumes of imaging data annotated by expert radiologists. Data challenges engage the radiology community to develop such datasets, which provide the standard of truth in training AI systems to perform tasks relevant to diagnostic imaging. 

In a challenge, researchers compete on how well their AI models perform specific tasks such as detection, localization and categorization of abnormal features according to defined performance measures. Each AI challenge explores and demonstrates the ways AI can benefit radiology and improve patient care.

These AI data challenges are organized by the RSNA Radiology Informatics Committee, often in collaboration with other radiological organizations from around the world. Please direct questions about the AI data challenge program to


How does an AI challenge work?

There are two main phases of an AI challenge: training and evaluation. 

In the training phase, researchers develop models and run them against the labeled data to get feedback on how closely their results match the expert annotations. In the evaluation phase, models are evaluated and scored against a portion of the dataset without labels. Winners are determined based on their scores in this phase.


RSNA Cervical Spine Fracture AI Challenge

The 2022 RSNA Cervical Spine Fracture AI Challenge invites participants to explore whether AI can be used to aid in the detection and localization of cervical spine fractures.

Quickly detecting and determining the location of vertebral fractures is essential to prevent neurologic deterioration and paralysis after trauma, which is why RSNA, the American Society of Neuroradiology and the American Society of Spine Radiology are co-hosting the Cervical Spine Fracture AI Challenge.

Participants of the 2022 competition are challenged to develop machine learning models that match the radiologists' performance in detecting and localizing fractures in the seven vertebrae that comprise the cervical spine.

Learn more about the 2022 AI Challenge and submit your entries by Oct. 27.

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Past AI challenges

View information about past challenges here:

2021: COVID-19 AI Detection Challenge
About the COVID-19 AI Detection Challenge  
Dataset description 

2021: Brain Tumor AI Challenge 
About the Brain Tumor AI Challenge 
Dataset description

2020: RSNA Pulmonary Embolism Detection Challenge
About the Pulmonary Embolism Detection Challenge 
Dataset description  

2019: RSNA Intracranial Hemorrhage Detection Challenge 
About the Intracranial Hemorrhage Detection Challenge 
Dataset description 

2018: RSNA Pneumonia Detection Challenge
About the Pneumonia Detection Challenge  
Dataset description  
2017: RSNA Pediatric Bone Age Challenge 
About the Pediatric Bone Age Challenge 
Dataset description