Artificial Intelligence, Augmented Reality, and Virtual Reality Advances and Applications in Interventional Radiology

Abstract

Artificial intelligence (AI) uses computer algorithms to process and interpret data as well as perform tasks, while continuously redefining itself. Machine learning, a subset of AI, is based on reverse training in which evaluation and extraction of data occur from exposure to labeled examples. AI is capable of using neural networks to extract more complex, high-level data, even from unlabeled data sets, and better emulate, or even exceed, the human brain. Advances in AI have and will continue to revolutionize medicine, especially the field of radiology. Compared to the field of interventional radiology, AI innovations in the field of diagnostic radiology are more widely understood and used, although still with significant potential and growth on the horizon. Additionally, AI is closely related and often incorporated into the technology and programming of augmented reality, virtual reality, and radiogenomic innovations which have the potential to enhance the efficiency and accuracy of radiological diagnoses and treatment planning. There are many barriers that limit the applications of artificial intelligence applications into the clinical practice and dynamic procedures of interventional radiology. Despite these barriers to implementation, artificial intelligence in IR continues to advance and the continued development of machine learning and deep learning places interventional radiology in a unique position for exponential growth. This review describes the current and possible future applications of artificial intelligence, radiogenomics, and augmented and virtual reality in interventional radiology while also describing the challenges and limitations that must be addressed before these applications can be fully implemented into common clinical practice.

An evaluation of intelligent and immersive digital applications in eliciting cognitive states in humans through the utilization of Emotiv Insight

“…According to Ende et al [ 16 ], AI is frequently included in VR, AR, and radiogenomics programming and technology because it can enhance the precision and effectiveness of radiological therapy and diagnosis planning. AI is becoming more and more used in radiology, even though it has numerous limits in the medical industry.…”

Inovações no treinamento cirúrgico: explorando o papel da inteligência artificial e dos grandes modelos de linguagem (LLM)

“…A IA está desempenhando um papel importante no avanço dos sistemas de realidade virtual (VR) e realidade aumentada (AR), especialmente no campo do treinamento cirúrgico. Essas tecnologias imersivas oferecem cenários de treinamento realistas e interativos, que podem se assemelhar a procedimentos cirúrgicos da vida real [24][25][26] Essa lacuna é significativa, porque a comunicação eficaz é um aspecto crítico do treinamento cirúrgico, e abordála pode levar a melhorias consideráveis na experiência de aprendizado e nos resultados dos treinandos 28,29 .…”

Perspective Chapter: 5G Enabling Technologies – Revolutionizing Transport, Environment, and Health

“…Asif Khan et al [16] presented a comprehensive survey of recent developments in MEC-enabled video streaming bringing unprecedented improvement to enable novel use cases. von Ende et al [17] described the present and potential future applications of radiogenomics, augmented and virtual reality, and artificial intelligence in interventional radiology, along with the issues and constraints that need to be resolved before these applications can be fully integrated into standard clinical practice.…”