Surgical workflow image generation based on generative adversarial networks

doi:10.1109/ICAIBD.2018.8396171

	Surgical workflow image generation based on generative adversarial networks
	Chen, Yuwen1 ; Zhong, Kunhua1 ; Wang, Fei 2; Wang, Hongqian 2; Zhao, Xueliang1
	2018
会议日期	May 26, 2018 - May 28, 2018
会议地点	Chengdu, China
DOI	10.1109/ICAIBD.2018.8396171
页码	82-86
英文摘要	In the medical field, the labeling of surgical video data requires Expert knowledge, collecting enough numbers of marked surgical video data is difficult and time-consuming. The insufficient video data (labeled data) leads to the low generalization ability of the training model and the low accuracy of recognition. It has been recently shown that Generative Adversarial Networks (GANs) can produce synthetic images of exceptional visual fidelity. In this work, the authors propose the GAN-based method for automatic Surgical Workflow images. The theory and methodology of this paper are validated on real three surgery video datasets. It can generative effective surgical workflow images. The technology studied in this paper has broad application prospects in computer-aided surgical systems and is a core component of the artificial intelligence medical operating room in the future. © 2018 IEEE.
会议录	2018 International Conference on Artificial Intelligence and Big Data, ICAIBD 2018
语种	英语
内容类型	会议论文
源URL	[http://119.78.100.138/handle/2HOD01W0/7954]
专题	中国科学院重庆绿色智能技术研究院
作者单位	1.University of Chinese Academy of Sciences, Chengdu Institute of Computer Application, Chinese Academy of Sciences, High Performance Computing Application RandD Center, Chongqing Institute of Green and Intelligent, Chongqing, China; 2.Information Department, Southwest Hospital, Chongqing, China
推荐引用方式 GB/T 7714	Chen, Yuwen,Zhong, Kunhua,Wang, Fei,et al. Surgical workflow image generation based on generative adversarial networks[C]. 见:. Chengdu, China. May 26, 2018 - May 28, 2018.