Lab profile
About Artificial Intelligence Imaging Research Center
The center transforms pediatric healthcare by leveraging artificial intelligence and fostering cross-disciplinary collaboration to develop AI-powered imaging solutions that improve diagnostic accuracy, object detection, early interventions, and personalized treatments. They are building one of the largest repositories of clinical pediatric imaging data and developing AI tools for bone age assessment, line/drain/airway identification, liver fibrosis scoring, and organ segmentation in pediatric scans.
01 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
02 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- Radiomic Features Extracted From Manual and Deep Learning-Based Segmentations: Comparison of Agreement, Bias, and Model Performance.AJR. American journal of roentgenology · 2026
- Review of Artificial Intelligence for Automated Assessment of Lines, Drains, and Airways on Pediatric and Adult Chest Radiographs.Pediatric reports · 2026
- A two-stage deep learning pipeline for automated detection and localization of endotracheal tubes on pediatric chest radiographs: a pilot study.Pediatric radiology · 2026
Active NIH grants
- MRI Phenotyping of Severe BPD and Prediction of OutcomesJason C. Woods · NHLBI · FY 2026
- Digital Innovation, Simulation, and Collaboration using Virtual Environment Realities (DISCOVER) for Pediatric DiagnosticMaya Dewan · AHRQ · FY 2026
03 · Updates
Updates and lab news
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04 · Official presence
Lab sources and channels
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05 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.