Artificial Intelligence Applications in Medical Imaging: A Review of the Medical Physics Research, Including: Dentist, Health Assistant, Medical Sterilization Specialist, Dental Hygiene, Cardiac Technologist and nursing

Abstract

Artificial intelligence (AI) has emerged as a transformative force in medical imaging, enhancing diagnostic capabilities, streamlining clinical workflows, and improving patient outcomes. This review explores the significant advancements of AI in various imaging modalities, including X-ray, CT, MRI, ultrasound, and PET imaging, highlighting its application in disease detection, image segmentation, and radiation dose optimization. AI-driven systems, particularly those utilizing deep learning techniques such as Convolutional Neural Networks (CNNs), have shown impressive results in detecting a range of diseases, including cancer, lung diseases, and fractures, while also improving image quality and reducing noise in scans. Despite the promising potential, challenges remain, including data privacy concerns, biases in datasets, and the need for regulatory standards to ensure safe and effective integration. Furthermore, this review discusses the evolving role of medical physicists in AI integration and the future direction of AI in medical imaging, including advancements in algorithms, the integration with other technologies, and the potential for personalized medicine. The continued development and collaboration between AI developers and healthcare providers are essential for the successful adoption of AI in clinical practice, promising a new era in precision healthcare.