Scalable gastroscopic video summarization via similar-inhibition dictionary selection

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	Scalable gastroscopic video summarization via similar-inhibition dictionary selection
	Wang S(王帅); Cong Y(丛杨); Cao, Jun; Yang YS(杨云生); Tang YD(唐延东); Zhao HC(赵怀慈); Yu HB(于海斌)
刊名	ARTIFICIAL INTELLIGENCE IN MEDICINE
	2016
卷号	66 页码:1-13
关键词	Video summarization Key frame Similar-inhibition dictionary selection Image attention prior Gastroscopic video
ISSN号	0933-3657
通讯作者	王帅
产权排序	1
中文摘要	Objective: This paper aims at developing an automated gastroscopic video summarization algorithm to assist clinicians to more effectively go through the abnormal contents of the video. Methods and materials: To select the most representative frames from the original video sequence, we formulate the problem of gastroscopic video summarization as a dictionary selection issue. Different from the traditional dictionary selection methods, which take into account only the number and reconstruction ability of selected key frames, our model introduces the similar-inhibition constraint to reinforce the diversity of selected key frames. We calculate the attention cost by merging both gaze and content change into a prior cue to help select the frames with more high-level semantic information. Moreover, we adopt an image quality evaluation process to eliminate the interference of the poor quality images and a segmentation process to reduce the computational complexity. Results: For experiments, we build a new gastroscopic video dataset captured from 30 volunteers with more than 400k images and compare our method with the state-of-the-arts using the content consistency, index consistency and content-index consistency with the ground truth. Compared with all competitors, our method obtains the best results in 23 of 30 videos evaluated based on content consistency, 24 of 30 videos evaluated based on index consistency and all videos evaluated based on content-index consistency. Conclusions: For gastroscopic video summarization, we propose an automated annotation method via similar-inhibition dictionary selection. Our model can achieve better performance compared with other state-of-the-art models and supplies more suitable key frames for diagnosis. The developed algorithm can be automatically adapted to various real applications, such as the training of young clinicians, computer aided diagnosis or medical report generation. (C) 2015 Elsevier B.V. All rights reserved.
WOS标题词	Science & Technology ; Technology ; Life Sciences & Biomedicine
类目[WOS]	Computer Science, Artificial Intelligence ; Engineering, Biomedical ; Medical Informatics
研究领域[WOS]	Computer Science ; Engineering ; Medical Informatics
关键词[WOS]	WIRELESS CAPSULE ENDOSCOPY ; SHOT-BOUNDARY DETECTION ; KEY FRAME EXTRACTION ; CLASSIFICATION ; VISUALIZATION ; ABSTRACTION ; FEATURES ; SEGMENTATION ; IMAGES
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000371368900001
内容类型	期刊论文
源URL	[http://ir.sia.cn/handle/173321/17733]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Wang S,Cong Y,Cao, Jun,et al. Scalable gastroscopic video summarization via similar-inhibition dictionary selection[J]. ARTIFICIAL INTELLIGENCE IN MEDICINE,2016,66:1-13.
APA	Wang S.,Cong Y.,Cao, Jun.,Yang YS.,Tang YD.,...&Yu HB.(2016).Scalable gastroscopic video summarization via similar-inhibition dictionary selection.ARTIFICIAL INTELLIGENCE IN MEDICINE,66,1-13.
MLA	Wang S,et al."Scalable gastroscopic video summarization via similar-inhibition dictionary selection".ARTIFICIAL INTELLIGENCE IN MEDICINE 66(2016):1-13.