Abstract

Artificial intelligence (AI) in medical physics is seeing unprecedented growth in increasing the accuracy of medical imaging and radiation therapy. In medical imaging, AI utilizes techniques such as deep learning and neural networks to improve the quality of images captured by imaging devices such as magnetic resonance imaging (MRI) and computed tomography (CT), allowing clinicians to more easily detect tumors and other diseases in their earliest stages. All because of advanced algorithms, the resolution of images can be increased and noise reduced so that small abnormalities are easily identified that would not be visible with traditional methods. AI assists in improving treatment planning by identifying the exact location and size of tumors and the allocation of doses of radiation based on the distinctive characteristics of each patient. Through machine learning, algorithms are applied to optimize the distribution and precise pointing of the radiation to minimize damage to normal tissue, thereby minimizing side effects and maximizing treatment effectiveness. AI also enables improved integration in this area with other technologies such as virtual reality and 3D printing, which may improve the accuracy of diagnosis and therapy and provide a personalized treatment experience in line with the needs of each patient.