Document Detail


Hysteroscopy video summarization and browsing by estimating the physician's attention on video segments.
MedLine Citation:
PMID:  21920798     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
Specialists often need to browse through libraries containing many diagnostic hysteroscopy videos searching for similar cases, or even to review the video of one particular case. Video searching and browsing can be used in many situations, like in case-based diagnosis when videos of previously diagnosed cases are compared, in case referrals, in reviewing the patient records, as well as for supporting medical research (e.g. in human reproduction). However, in terms of visual content, diagnostic hysteroscopy videos contain lots of information, but only a reduced number of frames are actually useful for diagnosis/prognosis purposes. In order to facilitate the browsing task, we propose in this paper a technique for estimating the clinical relevance of video segments in diagnostic hysteroscopies. Basically, the proposed technique associates clinical relevance with the attention attracted by a diagnostic hysteroscopy video segment during the video acquisition (i.e. during the diagnostic hysteroscopy conducted by a specialist). We show that the resulting video summary allows specialists to browse the video contents nonlinearly, while avoiding spending time on spurious visual information. In this work, we review state-of-art methods for summarizing general videos and how they apply to diagnostic hysteroscopy videos (considering their specific characteristics), and conclude that our proposed method contributes to the field with a summarization and representation method specific for video hysteroscopies. The experimental results indicate that our method tends to produce compact video summaries without discarding clinically relevant information.
Authors:
Wilson Gavião; Jacob Scharcanski; Jan-Michael Frahm; Marc Pollefeys
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-8-24
Journal Detail:
Title:  Medical image analysis     Volume:  -     ISSN:  1361-8423     ISO Abbreviation:  -     Publication Date:  2011 Aug 
Date Detail:
Created Date:  2011-9-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9713490     Medline TA:  Med Image Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 Elsevier B.V. All rights reserved.
Affiliation:
Instituto de Informática, Universidade Federal do Rio Grande do Sul, Avenida Bento Gonçalves, 9500, 91501-970 Porto Alegre, RS, Brazil.
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