Innovating Pediatric Imaging with AI and Cross-Disciplinary Collaboration
At Cincinnati Children's Artificial Intelligence Imaging Research Center, we are transforming pediatric healthcare by leveraging artificial intelligence (AI) and fostering collaboration across various departments and divisions. Our AI-powered imaging solutions can help improve diagnostic accuracy, object detection, support early interventions and personalized treatments for the children of Cincinnati and beyond.
By integrating expertise from multiple departments and divisions, we address a broad range of pediatric health challenges—from early disease detection to disease progression tracking and personalized treatment planning. Our AI tools are changing the landscape of pediatric diagnostics and care, including:
- Using over 40,000 pediatric hand radiographs to develop modern AI systems to improve bone age assessments
- An AI algorithm that automatically identifies and locates lines, drains and airways (LDAs) in pediatric chest radiographs for our most critically ill children
- An AI model that automates histologic liver fibrosis scoring of pediatric biopsy samples, improving diagnosis, minimizing inter-observer variability and helping direct treatment
- Automating segmentation of numerous organs and tissues in pediatric CT and MRI scans for organs (e.g., liver, spleen, pancreas, heart, lungs, airways, fat and muscle)
We’re also developing one of the largest repositories of clinical pediatric imaging data, including radiology, cardiology, histology and endoscopy images, as well as associated clinical data such as laboratory results and "-omics" data.
In addition to our research, we help enhance imaging-focused AI capabilities of other Cincinnati Children’s faculty and staff.
