Recent innovations in artificial intelligence-driven imaging techniques are significantly improving diagnostic precision in pediatric medicine. Deep learning models have enhanced stroke lesion segmentation and elevated the quality of MRI and ultrasound imaging for children, offering better assessment of conditions like renal ultrasounds, abdominal trauma, neuroimaging, and brain hemorrhages. These developments promise to facilitate earlier diagnosis and improve patient outcomes in critical pediatric care scenarios.