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The Integration of Artificial Intelligence (AI) Into Pediatric Imaging
0
Zitationen
3
Autoren
2025
Jahr
Abstract
The integration of artificial intelligence (AI) into pediatric imaging marks a significant advancement in radiology, addressing unique challenges in diagnosing children. This discussion highlights the newest AI algorithms in diagnostics like CT, MRI, and ultrasound, emphasizing machine and deep learning's role in enhancing image analysis for detecting anomalies such as tumors or organ irregularities. AI improves pattern recognition, supports radiologists, and provides augmented diagnostic results. Radiation safety, a critical concern in pediatric imaging, benefits from AI's dose optimization capabilities, with studies showing a 36%-70% reduction in CT scan exposure without quality loss. Generative adversarial networks (GANs) enhance image reconstruction, segmentation, and diagnosis, offering performance improvements of up to 158.6%. However, methodological limitations and insufficient research on dose optimization and broader AI applications highlight the need for thorough validation and further studies to maximize AI's potential in pediatric radiology.
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