| Semantic Localization-driven Partial Image Retrieval in CT Series. | |
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MedLine Citation:
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PMID: 23154618 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Background: Picture archiving and communication systems (PACS) contain very large amounts of computed tomography (CT) data. When querying a PACS for a particular series, the user is often not interested in the complete series but in a certain region of interest (ROI), described e.g. by an example view in another series or an anatomical concept. Objectives: Restricting a retrieval query to such an ROI saves both loading time and navigational effort. In this paper, we propose an efficient method for defining and retrieving ROIs. Methods: We employ interpolation and regression techniques for mapping the slices of a series to a newly generated standardized height atlas of the human body. Results: Examinations of the accuracy and the saved input/output (I/O) costs of our new method on a repository of 1,360 CT series demonstrate the advantages of our system. Depending on the scope of the retrieval query, we can economize up to 99% of the total loading time. Conclusion: Our proposed method for flexible, context-based, partial image retrieval enables the user to directly focus on the relevant portion of the image material and it targets the high potential of I/O cost reduction of a common PACS. |
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Authors:
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A Cavallaro; H-P Kriegel; M Petri; M Schubert |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-11-16 |
Journal Detail:
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Title: Methods of information in medicine Volume: 51 ISSN: 0026-1270 ISO Abbreviation: Methods Inf Med Publication Date: 2012 Nov |
Date Detail:
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Created Date: 2012-11-16 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0210453 Medline TA: Methods Inf Med Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Marisa Petri, Institute for Informatics, Ludwig-Maximilians-Universität München, Oettingenstr. 67, 80538 Munich, Germany, E-mail: petri@dbs.ifi.lmu.de. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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