Čes-slov Pediat 2025, 80(5):219-225 | DOI: 10.55095/CSPediatrie2025/042

Artificial intelligence in imaging methods

Lukáš Lambert, Vojtěch Suchánek, Lukáš Mikšík, Jana Svítilová

Klinika zobrazovacích metod, Fakultní nemocnice v Motole, 2. lékařská fakulta Univerzity Karlovy, Praha

Recent advances in artificial intelligence (AI) have introduced novel opportunities in diagnostic imaging, aiming to enhance diagnostic accuracy, optimize resource utilization, and improve patient comfort. While AI concepts have existed for decades, only recent improvements in computational power have enabled their widespread integration into clinical workflows. This article reviews key applicatio

ns of AI in pediatric radiology-a field where the limited availability of high-quality annotated training data remains a major constraint.

AI technologies are being deployed across various stages of the imaging process: from optimizing examination requests and scheduling, through contactless biometric monitoring during acquisition, to advanced image reconstruction techniques that enable reduced radiation exposure and shorter scan times. In image interpretation, AI supports pathology detection, facilitates quantitative assessments (e.

g., skeletal age estimation, anthropometric analysis), and aids in the standardization and clearer communication of findings to both clinicians and patients.

While AI cannot substitute the clinical expertise of trained radiologists, its complementary role is steadily expanding, offering substantial benefits across various aspects of imaging practice. Nonetheless, significant challenges remain-particularly in the domains of ethical governance, diagnostic accountability, and long-term economic sustainability.

Keywords: artificial intelligence, pediatric radiology, X-ray, computed tomography, magnetic resonance imaging, contrast media

Accepted: September 3, 2025; Published: June 1, 2025  Show citation