Localized multiscale texture based retrieval of neurological image

Sidong Liu*, Lei Jing, 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

3 Citations (Scopus)

Abstract

The volume and complexity of neurological images have significantly increased, which leads to challenges in efficient data management and retrieval. In this paper, we developed a new content-based image retrieval framework with the localized multiscale Discrete Curvelet Transform (DCvT) features extracted from parametric neurological images. We also compared the performance of three different irregular-to-regular shape padding methods. 142 patient data with neurodegenerative disorders were used in the evaluation. The preliminary results show that our proposed framework supports fast neuroimaging retrieval, and the orthographic projection method can reduce the computational complexity and has a great potential to improve the retrieval for indefinite cases.

Original languageEnglish
Title of host publicationProceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages243-248
Number of pages6
ISBN (Electronic)9781424491681
ISBN (Print)9781424491667, 9781424491674
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 - Perth, Australia
Duration: 12 Oct 201015 Oct 2010

Conference

Conference23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
CountryAustralia
CityPerth
Period12/10/1015/10/10

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