Surgical tool detection
4 papers with code • 1 benchmarks • 2 datasets
Presence detection of various classes of surgical instruments in endoscopy videos.
Mutually leveraging both low-level feature sharing and high-level prediction correlating, our MTRCNet-CL method can encourage the interactions between the two tasks to a large extent, and hence can bring about benefits to each other.
Ranked #2 on Surgical tool detection on Cholec80
In the literature, two types of features are typically used to perform this task: visual features and tool usage signals.
Ranked #4 on Surgical tool detection on Cholec80
Results: We build a baseline tracker on top of the CNN model and demonstrate that our approach based on the ConvLSTM outperforms the baseline in tool presence detection, spatial localization, and motion tracking by over 5. 0%, 13. 9%, and 12. 6%, respectively.
Ranked #1 on Surgical tool detection on Cholec80
We propose a deep architecture, trained solely on image level annotations, that can be used for both tool presence detection and localization in surgical videos.
Ranked #3 on Surgical tool detection on Cholec80