Intracranial hemorrhage, or ICH, is an urgent condition in which there is bleeding within the brain’s cellular tissue and the spaces within the membranes surrounding the brain. As with other forms of stroke, speed and accuracy of diagnosis are essential to appropriate care. ICH 30-day mortality ranges from 35%- 52% with half of this mortality occurring within the first 24 hours. Faster turnaround times from diagnostic radiologists can speed emergency care decisions.
Robust AI model
Model trained and validated on data from hundreds of imaging facilities across the US.
Seamless Workflow Integration
Designed for integration using industry standard APIs. Clinical workflow change not required.
Can be deployed behind the firewall onsite or via cloud.
What It Does
How It Works
The deep learning algorithm uses a three-dimensional joint convolutional neural network (CNN) and convolutional recurrent neural network (ConvRNN) architecture for automatic ICH binary classification.
The resulting AI model was trained from about 3800 head CT scans collected from multiple clinical sites in both US and China, covering major imaging scanner varieties in the world.
The training data from the US were collected from 523 different imaging facilities from almost all states in the US.
Head CT Scans
Head CT Scans
How It Was Validated
A retrospective, blinded, multisite clinical validation study was conducted to evaluate the clinical performance of CuraRad-ICH.
Analysis of 388 CT studies collected from over 296 imaging facilities across 48 states in the US demonstrates system sensitivity and specificity of 90.6% and 93.1%, respectively. The average per-case processing time was 43 seconds.