Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12016
Title: Localized multiscale texture based retrieval of neurological image
Authors: Liu, S
Jing, L
Cai, W
Wen, L
Eberl, S
Fulham, M
Feng, D
Keywords: Computational complexity
Content-based retrieval
Feature extraction
Image retrieval
Medical disorders
Issue Date: 2010
Publisher: IEEE
Source: 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems (CBMS), 12-15 October 2010, Perth, WA, p. 243-248 How to cite?
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.
URI: http://hdl.handle.net/10397/12016
ISBN: 978-1-4244-9167-4
ISSN: 1063-7125
DOI: 10.1109/CBMS.2010.6042649
Appears in Collections:Conference Paper

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