Artificial Intelligence in Fetal and Pediatric Echocardiography

Area of Science:

• Cardiology
• Medical Imaging
• Artificial Intelligence

Background:

• Echocardiography is crucial for diagnosing fetal and pediatric heart conditions.
• Limitations include operator variability and interpretation complexity.
• Shortages of expert sonographers and cardiologists exist in some regions.

Purpose of the Study:

• To review current applications of AI in fetal and pediatric echocardiography.
• To identify challenges hindering AI adoption.
• To discuss future directions for AI integration.

Main Methods:

• Review of existing literature on AI in echocardiography.
• Analysis of AI's role in image acquisition, segmentation, and disease detection.
• Discussion of challenges and future prospects.

Main Results:

• AI, including machine learning and deep learning, shows potential to automate echocardiography tasks.
• AI can assist in congenital heart disease detection and measurements.
• Current challenges include limited datasets and algorithm transparency.

Conclusions:

• AI offers significant potential to enhance fetal and pediatric echocardiography.
• Addressing challenges like data availability and physician trust is essential for widespread AI integration.
• Future work should focus on overcoming these barriers for clinical implementation.