: Capable of real-time detection but had lower recall (missed some gauze).
: Miscounting gauze is a common human error in surgery; this paper proposes an automated AI system to track gauze in real-time using laparoscopic camera feeds. VID - 0011-1.mp4
Gauze Detection and Segmentation in Minimally Invasive Surgery Video Using Convolutional Neural Networks : Capable of real-time detection but had lower
Published in July 2022, this study addresses the critical medical challenge of —specifically surgical gauze left inside patients after laparoscopic procedures. Key Findings of the Paper: Key Findings of the Paper: : Identified as
: Identified as the best compromise, achieving an Intersection over Union (IoU) of 0.85 while running at over 30 frames per second (FPS), making it suitable for live surgical use.
The video file is a specific sample from the Gauze Detection and Segmentation dataset used in surgical computer vision research. The primary academic paper associated with this video is:
: The researchers created a specialized dataset featuring 4,003 hand-labeled frames from laparoscopic videos, including the "VID-0011-1" sequence, to train and test their models. Model Performance :