Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1870
PIRA download icon_1.1View/Download Full Text
DC FieldValueLanguage
dc.contributorDepartment of Electronic and Information Engineering-
dc.creatorKim, J-
dc.creatorCai, W-
dc.creatorFeng, DD-
dc.creatorWu, H-
dc.date.accessioned2014-12-11T08:25:34Z-
dc.date.available2014-12-11T08:25:34Z-
dc.identifier.issn1089-7771-
dc.identifier.urihttp://hdl.handle.net/10397/1870-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectFunctional imagingen_US
dc.subjectImage segmentationen_US
dc.subjectMultidimensional featuresen_US
dc.subjectRegion-based image retrievalen_US
dc.titleA new way for multidimensional medical data management : volume of interest (VOI)-based retrieval of medical images with visual and functional featuresen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationAuthor name used in this publication: Dagan Fengen_US
dc.description.otherinformationCentre for Multimedia Signal Processing, Department of Electronic and Information Engineeringen_US
dc.identifier.spage598-
dc.identifier.epage607-
dc.identifier.volume10-
dc.identifier.issue3-
dc.identifier.doi10.1109/TITB.2006.872045-
dcterms.abstractThe advances in digital medical imaging and storage in integrated databases are resulting in growing demands for efficient image retrieval and management. Content-based image retrieval (CBIR) refers to the retrieval of images from a database, using the visual features derived from the information in the image, and has become an attractive approach to managing large medical image archives. In conventional CBIR systems for medical images, images are often segmented into regions which are used to derive two-dimensional visual features for region-based queries. Although such approach has the advantage of including only relevant regions in the formulation of a query, medical images that are inherently multidimensional can potentially benefit from the multidimensional feature extraction which could open up new opportunities in visual feature extraction and retrieval. In this study, we present a volume of interest (VOI) based content-based retrieval of four-dimensional (three spatial and one temporal) dynamic PET images. By segmenting the images into VOIs consisting of functionally similar voxels (e.g., a tumor structure), multidimensional visual and functional features were extracted and used as region-based query features. A prototype VOI-based functional image retrieval system (VOI-FIRS) has been designed to demonstrate the proposed multidimensional feature extraction and retrieval. Experimental results show that the proposed system allows for the retrieval of related images that constitute similar visual and functional VOI features, and can find potential applications in medical data management, such as to aid in education, diagnosis, and statistical analysis.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on information technology in biomedicine, July 2006, v. 10, no. 3, p. 598-607-
dcterms.isPartOfIEEE transactions on information technology in biomedicine-
dcterms.issued2006-07-
dc.identifier.isiWOS:000239033000023-
dc.identifier.scopus2-s2.0-33746927523-
dc.identifier.pmid16871730-
dc.identifier.rosgroupidr32283-
dc.description.ros2006-2007 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
Appears in Collections:Journal/Magazine Article
Files in This Item:
File Description SizeFormat 
Kim_et_al_Visual_Functional_Features.pdf852.46 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show simple item record

Page views

85
Last Week
0
Last month
Citations as of Jul 3, 2022

Downloads

250
Citations as of Jul 3, 2022

SCOPUSTM   
Citations

37
Last Week
0
Last month
0
Citations as of Jun 30, 2022

WEB OF SCIENCETM
Citations

33
Last Week
0
Last month
0
Citations as of Jun 30, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.