New imaging techniques and trends in radiology.
Authors
Affiliations (3)
Affiliations (3)
- Atatürk University Faculty of Medicine, Department of Radiology, Erzurum, Türkiye.
- Erzincan Binali Yıldırım University Faculty of Medicine, Department of Radiology, Erzincan, Türkiye.
- Medipol University Faculty of Medicine, Department of Radiology, İstanbul, Türkiye.
Abstract
Radiography is a field of medicine inherently intertwined with technology. The dependency on technology is very high for obtaining images in ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI). Although the reduction in radiation dose is not applicable in US and MRI, advancements in technology have made it possible in CT, with ongoing studies aimed at further optimization. The resolution and diagnostic quality of images obtained through advancements in each modality are steadily improving. Additionally, technological progress has significantly shortened acquisition times for CT and MRI. The use of artificial intelligence (AI), which is becoming increasingly widespread worldwide, has also been incorporated into radiography. This technology can produce more accurate and reproducible results in US examinations. Machine learning offers great potential for improving image quality, creating more distinct and useful images, and even developing new US imaging modalities. Furthermore, AI technologies are increasingly prevalent in CT and MRI for image evaluation, image generation, and enhanced image quality.