Perceptions of Artificial Intelligence in Medical Imaging: A Cross-Sectional Survey of 1,800 Participants

Background: Artificial intelligence (AI) is increasingly integrated into medical imaging, offering potential improvements in diagnostic accuracy, workflow efficiency, and patient care. However, successful adoption depends on healthcare professionals’ perceptions, trust, and willingness to use AI tools. Objective: This study aimed to evaluate the awareness, perception, and acceptance of AI in medical imaging among healthcare professionals and related stakeholders, and to identify factors influencing trust, adoption, and perceived usefulness. Methods: A cross-sectional survey was conducted using a structured Google Forms questionnaire between July 14 and September 15, 2025. A total of 1800 participants, including radiologists, radiologic technologists, medical students, and other healthcare professionals, completed the survey. The questionnaire assessed demographics, AI awareness, perceived usefulness, trust, adoption willingness, and concerns regarding ethical, privacy, and professional implications. Data were analyzed using descriptive statistics, Chi-square tests, ANOVA, and logistic regression. Results: Awareness of AI applications was highest among radiologists (85%) and lowest among other healthcare professionals (40%). Seventy percent of respondents perceived AI as useful for diagnostic accuracy, while 60% were willing to adopt AI under human supervision. Key concerns included data privacy (55%), ethical and medico-legal issues (50%), algorithmic bias (48%), and job displacement (35%). Prior exposure to AI, professional role, and perceived usefulness significantly predicted willingness to adopt AI (p < 0.001). Conclusion: While healthcare professionals recognize AI’s clinical value, trust, ethical, and privacy concerns remain barriers to adoption. Targeted education, transparent AI models, and clear regulatory frameworks are essential for responsible integration.