In recent years, the healthcare sector has witnessed significant development due to the rapid advancement of artificial intelligence technologies. One of the most important modern applications in diagnostic medicine is the use of intelligent systems in medical image analysis. These technologies help physicians detect diseases at early stages and improve diagnostic accuracy, which positively affects the quality of healthcare services provided to patients. Artificial intelligence systems in medical imaging rely on advanced algorithms such as deep learning and artificial neural networks. These technologies are capable of analyzing X-ray images, MRI scans, and CT scans with high accuracy. By training these systems on thousands of medical images, they become able to recognize disease patterns and detect abnormalities or tumors that may sometimes be difficult for the human eye to notice. AI also helps reduce the time required to analyze medical images. Intelligent systems can process large amounts of medical data in a short period, enabling physicians to make faster and more accurate treatment decisions. Additionally, these technologies can assist doctors in monitoring disease progression and evaluating the effectiveness of various treatments. Despite the significant benefits of this technology, several challenges remain, including the need for reliable medical data and the protection of patient privacy. Furthermore, implementing such systems requires advanced technological infrastructure and specialized experts in both medicine and artificial intelligence. In conclusion, artificial intelligence in medical image analysis represents an important step toward improving healthcare systems and enhancing diagnostic accuracy. The use of these technologies is expected to expand in the future to support physicians and improve the quality of medical services worldwide.