Automated Microsurgical Tool Segmentation and Characterization in Intra-Operative Neurosurgical Videos
Author:
Affiliation:
1. IIIT-Bangalore,Surgical and Assistive Robotics Lab,Bangalore,India,560100
2. NIMHANS,Department of Neurosurgery,Bangalore,India,560029
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9870821/9870822/09871838.pdf?arnumber=9871838
Reference25 articles.
1. Automation of surgical skill assessment using a three-stage machine learning algorithm
2. A comparative analysis of multi-backbone Mask R-CNN for surgical tools detection
3. Association Between Surgeon Technical Skills and Patient Outcomes
4. A Guide to Annotation of Neurosurgical Intraoperative Video for Machine Learning Analysis and Computer Vision
5. Automated Vision-Based Microsurgical Skill Analysis in Neurosurgery Using Deep Learning: Development and Preclinical Validation
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2. Computer Assisted Phase Recognition of Micro-Neurosurgical Intraoperative Videos;2024 IEEE 37th International Symposium on Computer-Based Medical Systems (CBMS);2024-06-26
3. Real-Time Surgical Tool Classification and Characterization with Surface-EMG Signals;2024 16th International Conference on Computer and Automation Engineering (ICCAE);2024-03-14
4. SecureFrameNet:A rich computing capable secure framework for deploying neural network models on edge protected system.;The Third International Conference on Artificial Intelligence and Machine Learning Systems;2023-10-25
5. Automated Microsurgical Tool Categorization using a Surface-Based EMG System;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24
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