Document Detail


Intestinal motility assessment with video capsule endoscopy: automatic annotation of phasic intestinal contractions.
MedLine Citation:
PMID:  19423434     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Intestinal motility assessment with video capsule endoscopy arises as a novel and challenging clinical fieldwork. This technique is based on the analysis of the patterns of intestinal contractions shown in a video provided by an ingestible capsule with a wireless micro-camera. The manual labeling of all the motility events requires large amount of time for offline screening in search of findings with low prevalence, which turns this procedure currently unpractical. In this paper, we propose a machine learning system to automatically detect the phasic intestinal contractions in video capsule endoscopy, driving a useful but not feasible clinical routine into a feasible clinical procedure. Our proposal is based on a sequential design which involves the analysis of textural, color, and blob features together with SVM classifiers. Our approach tackles the reduction of the imbalance rate of data and allows the inclusion of domain knowledge as new stages in the cascade. We present a detailed analysis, both in a quantitative and a qualitative way, by providing several measures of performance and the assessment study of interobserver variability. Our system performs at 70% of sensitivity for individual detection, whilst obtaining equivalent patterns to those of the experts for density of contractions.
Authors:
Fernando Vilarino; Panagiota Spyridonos; Fosca Deiorio; Jordi Vitria; Fernando Azpiroz; Petia Radeva
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-05-05
Journal Detail:
Title:  IEEE transactions on medical imaging     Volume:  29     ISSN:  1558-254X     ISO Abbreviation:  IEEE Trans Med Imaging     Publication Date:  2010 Feb 
Date Detail:
Created Date:  2010-02-04     Completed Date:  2010-05-04     Revised Date:  2012-04-24    
Medline Journal Info:
Nlm Unique ID:  8310780     Medline TA:  IEEE Trans Med Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  246-59     Citation Subset:  IM    
Affiliation:
Computer Vision Center and Computer Science Department, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain.
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MeSH Terms
Descriptor/Qualifier:
Adult
Capsule Endoscopy / methods*
Gastrointestinal Motility / physiology*
Humans
Image Processing, Computer-Assisted / methods*
ROC Curve
Reproducibility of Results

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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