A robust volumetric feature extraction approach for 3D neuroimaging retrieval

Sidong Liu*, Weidong Cai, Lingfeng Wen, Stefan Eberl, Michael J. Fulham, Dagan Feng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

13 Citations (Scopus)

Abstract

The increased volume of 3D neuroimaging data has created a need for efficient data management and retrieval. We suggest that image retrieval via robust volumetric features could benefit managing these large image datasets. In this paper, we introduce a new feature extraction method, based on disorder-oriented masks, that uses the volumetric spatial distribution patterns in 3D physiological parametric neurological images. Our preliminary results indicate that the proposed volumetric feature extraction approach could support reliable 3D neuroimaging data retrieval and management.

Original languageEnglish
Title of host publication2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages5657-5660
Number of pages4
ISBN (Print)9781424441235
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10 - Buenos Aires, Argentina
Duration: 31 Aug 20104 Sept 2010

Conference

Conference2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10
Country/TerritoryArgentina
CityBuenos Aires
Period31/08/104/09/10

Fingerprint

Dive into the research topics of 'A robust volumetric feature extraction approach for 3D neuroimaging retrieval'. Together they form a unique fingerprint.

Cite this