| Automated topographic segmentation and transit time estimation in endoscopic capsule exams. | |
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MedLine Citation:
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PMID: 18270058 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Endoscopic capsule is a recent medical technology with important clinical benefits but suffering from a practical handicap: long exam annotation times. This paper proposes and compares two approaches (Bayesian and support vector machines) that can be used to segment the gastrointestinal tract into its four major topographic areas, allowing the automatic estimation of the clinically relevant gastric and intestinal sections and corresponding transit times. According to medical specialists, this can reduce exam annotation times by up to 12% (15 min). This automatic tool has been integrated into our CapView annotation software that is currently being used by three medical institutions. |
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Authors:
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J S Cunha; M Coimbra; P Campos; J M Soares |
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Publication Detail:
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Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: IEEE transactions on medical imaging Volume: 27 ISSN: 0278-0062 ISO Abbreviation: IEEE Trans Med Imaging Publication Date: 2008 Jan |
Date Detail:
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Created Date: 2008-02-13 Completed Date: 2008-03-11 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8310780 Medline TA: IEEE Trans Med Imaging Country: United States |
Other Details:
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Languages: eng Pagination: 19-27 Citation Subset: IM |
Affiliation:
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Department of Electronics, University of Aveiro, Aveiro, Portugal. jcunha@det.ua.pt |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Algorithms Artificial Intelligence Capsule Endoscopy / methods* Gastrointestinal Motility / physiology* Gastrointestinal Tract / anatomy & histology*, physiology* Humans Image Enhancement / methods Image Interpretation, Computer-Assisted / methods* Imaging, Three-Dimensional / methods* Pattern Recognition, Automated / methods* Reproducibility of Results Sensitivity and Specificity Time Factors User-Computer Interface |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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