Extended Reality in Diagnostic Imaging-A Literature Review.
Paulina KuklaKarolina MaciejewskaIga StrojnaMałgorzata ZapałGrzegorz ZwierzchowskiBartosz BąkPublished in: Tomography (Ann Arbor, Mich.) (2023)
The utilization of extended reality (ER) has been increasingly explored in the medical field over the past ten years. A comprehensive analysis of scientific publications was conducted to assess the applications of ER in the field of diagnostic imaging, including ultrasound, interventional radiology, and computed tomography. The study also evaluated the use of ER in patient positioning and medical education. Additionally, we explored the potential of ER as a replacement for anesthesia and sedation during examinations. The use of ER technologies in medical education has received increased attention in recent years. This technology allows for a more interactive and engaging educational experience, particularly in anatomy and patient positioning, although the question may be asked: is the technology and maintenance cost worth the investment? The results of the analyzed studies suggest that implementing augmented reality in clinical practice is a positive phenomenon that expands the diagnostic capabilities of imaging studies, education, and positioning. The results suggest that ER has significant potential to improve diagnostic imaging procedures' accuracy and efficiency and enhance the patient experience through increased visualization and understanding of medical conditions. Despite these promising advancements, further research is needed to fully realize the potential of ER in the medical field and to address the challenges and limitations associated with its integration into clinical practice.
Keyphrases
- endoplasmic reticulum
- medical education
- estrogen receptor
- high resolution
- breast cancer cells
- clinical practice
- healthcare
- computed tomography
- case report
- magnetic resonance imaging
- quality improvement
- working memory
- intensive care unit
- human health
- fluorescence imaging
- positron emission tomography
- acute respiratory distress syndrome
- climate change
- deep learning
- contrast enhanced