AI is transforming radiology and medical imaging, enhancing diagnosis speed and accuracy, according to Fariborz Faghihi, head of Radiology Technology at Shahid Beheshti University of Medical Sciences.
Faghihi emphasized that AI applications are being integrated into clinical education, enabling interactive learning experiences tailored to specific conditions. This technology is improving the training of radiologists and medical imaging professionals.
AI's role in radiology includes advanced image analysis, precise lesion detection, and efficient data interpretation. Deep learning algorithms, particularly Convolutional Neural Networks (CNN), are proving effective in identifying pathologies such as pneumonia and tumors.
AI assists in monitoring disease progression by analyzing quantitative measurements like tumor size and growth rates. Additionally, it aids in non-invasive imaging tests to evaluate cerebral blood flow, enhancing treatment strategies for conditions like acute ischemic stroke.
Faghihi noted that AI reduces diagnostic errors and enhances consistency among radiologists. Despite its advancements, he stressed that AI cannot replace the clinical judgment and empathy of radiologists, as human oversight remains essential in ensuring accurate diagnoses.