Point of Care Lung ultrasound has proven in multiple studies to be superior to CXR to diagnose pneumonia in children especially in limited resource settings. This non-radiating, portable and adaptable technique, brings an opportunity to detect pneumonia with higher accuracy than CXR. Ultrasound imaging interpretation is challenging. To deal with this complexity, we created a "brightness profiles" data reduction technique to identify specific anatomical structures identified by lung ultrasound using artificial intelligence. We use this technique to demonstrate how data reduction can help identify common anatomical landmarks and abnormal findings, and aid in the interpretation of ultrasound diagnosed pediatric pneumonia.
SPR 2022 Annual Meeting & Postgraduate Course