Open AccessUsing Virtual Reality and Machine Learning Techniques to Visualize the Human Spine
Author(s) -
Lin Hall,
Ping Wang,
Grayson Morgan Blankenship,
Emmanuel Zenil Lopez,
Clinton Castro,
Zhen Zhu,
Rui Wu
Publication year - 2021
Publication title -
epic series in computing
Language(s) - English
Resource type - Conference proceedings
ISSN - 2398-7340
DOI - 10.29007/xmcf
Subject(s) - computer science , virtual reality , position (finance) , visualization , artificial intelligence , human–computer interaction , rotation (mathematics) , machine learning , position paper , computer vision , world wide web , finance , economics
Machine learning technique usage has exploded in recent years, as has the utilization of virtual reality techniques. One area that these tools can be utilized is the practice of medicine. In this research, we propose a framework to visualize the position and rotation of human spines based on machine learning predictions. This framework approach is signifi- cant due to the importance of medical visualizations and organ tracking, with uses ranging from education of medical students, to surgical uses. Subsequently, using machine learning techniques with virtual reality offers real-time medical visualizations which is significant for surgery. According to our experiment results, our proposed framework can accurately predict position and rotation data.