Artificial Intelligence in Radiology
AI in Radiology
Keywords:
Radiology, artificial intelligence, machine learning, deep learning, radiomicsAbstract
In radiology and undoubtedly in radiologic anatomy, artificial intelligence (AI) plays an important role in the diagnostic and therapeutic processes by offering revolutionary innovations in the field of imaging. AI algorithms enhance accuracy, speed, and efficiency by analyzing images obtained through methods such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). Specifically, deep learning (DL) and machine learning (ML) applications enable early diagnosis by detecting fine details. This not only ensures patient safety but also alleviates the workload of radiologists and improves cost-effectiveness. Furthermore, AI offers safer imaging opportunities by reducing radiation doses and improving low-quality images. However, limitations such as data quality, ethical concerns, and patient privacy complicate the integration of AI into healthcare systems. In the future, AI is expected to expand its applications in radiology, offering more accurate diagnostic and therapeutic possibilities.
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