@inproceedings{1f93f0bc1b2348c29a24d2cdcae4953e,
title = "A vision-based surgical instruments classification system",
abstract = "This paper presents a real-time and automatic online vision-based surgical instruments recognition system, which can be used for surgical instruments monitoring during surgery or robotic applications. The main processes of this system consist of feature extraction and classification. In feature extraction, the image of surgical instruments placed on surgical drape are segmented by using color information. Several shape and contour information of the instruments are extracted as features. A two-stage classification scheme based on na{\"i}ve Bayesian classifier is then proposed to recognize the surgical instruments according to these features. Experimental results demonstrate that the proposed classification scheme can achieve 90.82% accuracy for classifying 7 instruments.",
keywords = "Na{\"i}ve Bayesian Classifier, Surgical assist systems, object classification, surgical instruments monitoring",
author = "Liu, {Xian Heng} and Hsieh, {Chung Hung} and Lee, {Jiann Der} and Lee, {Shin Tseng} and Wu, {Chieh Tsai}",
year = "2014",
doi = "10.1109/ARIS.2014.6871520",
language = "英语",
isbn = "9781479958467",
series = "2014 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2014",
publisher = "IEEE Computer Society",
pages = "18--22",
booktitle = "2014 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2014",
address = "美国",
note = "2014 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2014 ; Conference date: 06-06-2014 Through 08-06-2014",
}