2019/03/09 by Laura Fink, Sing Chun Lee, Fink, Laura +15
Computer Science · #Augmented Reality Applications #Computer Graphics and Visualization Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Graphics (cs.GR) #Medical Image Segmentation Techniques
paper · pdf · doi:10.48550/arxiv.1903.03837
openalex publication_date 2019/03/09 · openalex created_date 2022/07/24 · openalex updated_date 2026/07/28
With the increasing computational power of today's workstations, real-time\nphysically-based rendering is within reach, rapidly gaining attention across a\nvariety of domains. These have expeditiously applied to medicine, where it is a\npowerful tool for intuitive 3D data visualization. Embedded devices such as\noptical see-through head-mounted displays (OST HMDs) have been a trend for\nmedical augmented reality. However, leveraging the obvious benefits of\nphysically-based rendering remains challenging on these devices because of\nlimited computational power, memory usage, and power consumption. We navigate\nthe compromise between device limitations and image quality to achieve\nreasonable rendering results by introducing a novel light field that can be\nsampled in real-time on embedded devices. We demonstrate its applications in\nmedicine and discuss limitations of the proposed method. An open-source version\nof this project is available at https://github.com/lorafib/LumiPath which\nprovides full insight on implementation and exemplary demonstrational material.\n