Evaluating surgical skills from kinematic data using convolutional neural networks
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Updated
Nov 10, 2018 - Jupyter Notebook
Evaluating surgical skills from kinematic data using convolutional neural networks
SciKit-Surgery - Compact Libraries for Surgical Navigation
Code accompanying the paper "Deep Learning in Surgery - Assessing The Utility of Deep Neural Networks in Predicting Postoperative Surgical Complications: A Retrospective Study"
Globally reasoned multi-task model for surgical scene understanding. A multi-task model for segmentation and scene graph. Offical Implementation of "Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding", ICRA 2022 & RA-L.
Prototype improvement to robotic surgery by using muscle activation
Variable Life Adjusted Display and other risk-adjusted quality control charts
Run Raven2 robot with Unity3D and V-REP
ARAS-Farabi Experimental Framework for Skill Assessment in Capsulorhexis Surgery: The ARAS-Farabi Framework is designed to facilitate research in the area of skill assessment for Capsulorhexis surgery. This framework utilizes deep learning techniques for real-time performance in detecting and tracking the capsulorhexis cystotome and pupil.
High-performance GPU-based simulation platform for reinforcement learning with surgical robot learning
A python library for performing surgical skills evaluation
Automation of surgical tissue retraction via Machine Learning.
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