Surgical tool detection

5 papers with code • 1 benchmarks • 2 datasets

Presence detection of various classes of surgical instruments in endoscopy videos.

Most implemented papers

EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos

YuemingJin/TMRNet 9 Feb 2016

In the literature, two types of features are typically used to perform this task: visual features and tool usage signals.

Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos

CAMMA-public/ai4surgery 14 Jun 2018

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.

Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos

CAMMA-public/ConvLSTM-Surgical-Tool-Tracker 4 Dec 2018

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.

Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis

YuemingJin/MTRCNet-CL 13 Jul 2019

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.

A semi-supervised Teacher-Student framework for surgical tool detection and localization

mansoor-at/semi-supervised-surgical-tool-detection 21 Aug 2022

Therefore, in this paper we introduce a semi-supervised learning (SSL) framework in surgical tool detection paradigm which aims to mitigate the scarcity of training data and the data imbalance through a knowledge distillation approach.