Document Detail


Semantic Localization-driven Partial Image Retrieval in CT Series.
MedLine Citation:
PMID:  23154618     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
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.
Authors:
A Cavallaro; H-P Kriegel; M Petri; M Schubert
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-11-16
Journal Detail:
Title:  Methods of information in medicine     Volume:  51     ISSN:  0026-1270     ISO Abbreviation:  Methods Inf Med     Publication Date:  2012 Nov 
Date Detail:
Created Date:  2012-11-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0210453     Medline TA:  Methods Inf Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Affiliation:
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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