Computer-Aided WCE Diagnosis Using Convolutional Neural Network and Label Transfer

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 机器人学研究室

	Computer-Aided WCE Diagnosis Using Convolutional Neural Network and Label Transfer
	Wang Q(王强)1,2,3; Fan HJ(范慧杰)1,2; Tang YD(唐延东)1,2
	2019
会议日期	July 29 - August 2, 2019
会议地点	Suzhou, China
页码	581-585
英文摘要	Automatic diagnosis of gastropathy disease plays an important role in supporting the clinician and speeding up the examination process. While it is hard for clinicians to accurately detect gastrointestinal disease due to its great dependence on doctors experiences. In this paper, we propose an algorithm for stomach disease detection using deep learning features. First, images are partitioned into patches using a superpixel segmentation and points on superpixel edges are randomly selected as the center of image patches. Then a Convolutional Neural Network (CNN) is utilized to get more generic features of Wireless Capsule Endoscopy (WCE) stomach images. Finally, the detected patch label is transferred to superpixel labels to get a more accurate lesion detection area. Experiments on our database show that the proposed method can get more accurate disease regions and it outperforms the previous state-of-the-art methods based on hand-crafted features.
产权排序	1
会议录	Proceedings of 9th IEEE International Conference on CYBER Technology in Automation, Control, and Intelligent Systems
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-0769-1
WOS记录号	WOS:000569550300098
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26839]
专题	沈阳自动化研究所_机器人学研究室
通讯作者	Fan HJ(范慧杰)
作者单位	1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.University of Chinese Academy of Sciences, 100049, China
推荐引用方式 GB/T 7714	Wang Q,Fan HJ,Tang YD. Computer-Aided WCE Diagnosis Using Convolutional Neural Network and Label Transfer[C]. 见:. Suzhou, China. July 29 - August 2, 2019.