Scalable gastroscopic video summarization via similar-inhibition dictionary selection
文献类型：期刊论文
| 作者 | 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)
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| 刊名 | ARTIFICIAL INTELLIGENCE IN MEDICINE
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| 出版日期 | 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 |
| 产权排序 | 1 |
| 通讯作者 | 王帅 |
| 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 |
| 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. |
入库方式： OAI收割
来源：沈阳自动化研究所
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