Scalable gastroscopic video summarization via similar-inhibition dictionary selection | |
Wang S(王帅); Cong Y(丛杨)![]() ![]() ![]() ![]() | |
Department | 机器人学研究室 |
Source Publication | ARTIFICIAL INTELLIGENCE IN MEDICINE
![]() |
ISSN | 0933-3657 |
2016 | |
Volume | 66Pages:1-13 |
Indexed By | SCI ; EI |
EI Accession number | 20153701272071 |
WOS ID | WOS:000371368900001 |
Contribution Rank | 1 |
Funding Organization | National Science and Technology Support Program [2012BAI14B03] ; NSFC [61105013, 61375014, 61533015] ; Foundation of Chinese Scholarship Council |
Keyword | Video Summarization Key Frame Similar-inhibition Dictionary Selection Image Attention Prior Gastroscopic Video |
Abstract | 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. |
Language | 英语 |
WOS Headings | Science & Technology ; Technology ; Life Sciences & Biomedicine |
WOS Subject | Computer Science, Artificial Intelligence ; Engineering, Biomedical ; Medical Informatics |
WOS Keyword | WIRELESS CAPSULE ENDOSCOPY ; SHOT-BOUNDARY DETECTION ; KEY FRAME EXTRACTION ; CLASSIFICATION ; VISUALIZATION ; ABSTRACTION ; FEATURES ; SEGMENTATION ; IMAGES |
WOS Research Area | Computer Science ; Engineering ; Medical Informatics |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.sia.cn/handle/173321/17733 |
Collection | 机器人学研究室 |
Corresponding Author | Wang S(王帅) |
Affiliation | 1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Nanta Street 114, Shenyang, China 2.Department of Computer Science, Arizona State University, 1711 South Rural Road, Tempe, AZ, United States 3.Key Laboratory of Image Understanding and Computer Vision, Shenyang Institute of Automation, Chinese Academy of Sciences, Nanta Street 114, Shenyang, China 4.University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing, China 5.Department of Gastroenterology and Hepatology, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, China 6.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Nanta Street 114, Shenyang, China |
Recommended Citation 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. |
Files in This Item: | ||||||
File Name/Size | DocType | Version | Access | License | ||
Scalable gastroscopi(3367KB) | 期刊论文 | 作者接受稿 | 开放获取 | ODC PDDL | View Application Full Text |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment