Can I read Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos on EtoBox?

Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos by Shao, Zhimin; Xu, Jialang; Stoyanov, Danail; Mazomenos, Evangelos B.; Jin, Yueming is a scholarly article available to read on EtoBox.

What is Think Step by Step: Chain-of-Gesture Prompting for Error Detection in Robotic Surgical Videos about?

Despite significant advancements in robotic systems and surgical data science, ensuring safe and optimal execution in robot-assisted minimally invasive surgery (RMIS) remains a complex challenge. Current surgical error detection methods involve two parts: identifying surgical gestures and then detecting errors within each gesture clip. These methods seldom consider the rich contextual and semantic information inherent in surgical videos, limiting their performance due to reliance on accurate gesture identification. Motivated by the chain-of-thought prompting in natural language processing, this letter presents a novel and real-time end-to-end error detection framework, Chain-of-Thought (COG) prompting, leveraging contextual information from surgical videos. This encompasses two reasoning modules designed to mimic the decision-making processes of expert surgeons. Concretely, we first design a Gestural-Visual Reasoning module, which utilizes transformer and attention architectures for gesture prompting, while the second, a Multi-Scale Temporal Reasoning module, employs a multi-stage temporal convolutional network with both slow and fast paths for temporal information extraction. We e

Author

Shao, Zhimin; Xu, Jialang; Stoyanov, Danail; Mazomenos, Evangelos B.; Jin, Yueming

Published

2024

Language

EN