We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Toward Intraoperative Visual Intelligence: Real-Time Surgical Instrument Segmentation for Enhanced Surgical Monitoring.
- Authors
Daneshgar Rahbar, Mostafa; Pappas, George; Jaber, Nabih
- Abstract
Background: Open surgery relies heavily on the surgeon's visual acuity and spatial awareness to track instruments within a dynamic and often cluttered surgical field. Methods: This system utilizes a head-mounted depth camera to monitor surgical scenes, providing both image data and depth information. The video captured from this camera is scaled down, compressed using MPEG, and transmitted to a high-performance workstation via the RTSP (Real-Time Streaming Protocol), a reliable protocol designed for real-time media transmission. To segment surgical instruments, we utilize the enhanced U-Net with GridMask (EUGNet) for its proven effectiveness in surgical tool segmentation. Results: For rigorous validation, the system's performance reliability and accuracy are evaluated using prerecorded RGB-D surgical videos. This work demonstrates the potential of this system to improve situational awareness, surgical efficiency, and generate data-driven insights within the operating room. In a simulated surgical environment, the system achieves a high accuracy of 85.5% in identifying and segmenting surgical instruments. Furthermore, the wireless video transmission proves reliable with a latency of 200 ms, suitable for real-time processing. Conclusions: These findings represent a promising step towards the development of assistive technologies with the potential to significantly enhance surgical practice.
- Subjects
RESEARCH funding; QUANTITATIVE research; DESCRIPTIVE statistics; OPERATIVE surgery; INTRAOPERATIVE monitoring; ARTIFICIAL neural networks; DEEP learning; VISUAL acuity; SURGICAL instruments; DIGITAL image processing
- Publication
Healthcare (2227-9032), 2024, Vol 12, Issue 11, p1112
- ISSN
2227-9032
- Publication type
Article
- DOI
10.3390/healthcare12111112