Localized multiscale texture based retrieval of neurological image

Sidong Liu; Lei Jing; Weidong Cai; Lingfeng Wen; Stefan Eberl; Michael J. Fulham; Dagan Feng

doi:10.1109/CBMS.2010.6042649

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 proceeding › Conference proceeding contribution › peer-review

6 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 language	English
Title of host publication	Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	243-248
Number of pages	6
ISBN (Electronic)	9781424491681
ISBN (Print)	9781424491667, 9781424491674
DOIs	https://doi.org/10.1109/CBMS.2010.6042649
Publication status	Published - 1 Dec 2010
Externally published	Yes
Event	23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 - Perth, Australia Duration: 12 Oct 2010 → 15 Oct 2010

Conference

Conference	23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
Country/Territory	Australia
City	Perth
Period	12/10/10 → 15/10/10

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10.1109/CBMS.2010.6042649

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Liu, S., Jing, L., Cai, W., Wen, L., Eberl, S., Fulham, M. J., & Feng, D. (2010). Localized multiscale texture based retrieval of neurological image. In Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 (pp. 243-248). Article 6042649 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CBMS.2010.6042649

@inproceedings{5740be0a84ea4c0cab41773bfae4eaf4,

title = "Localized multiscale texture based retrieval of neurological image",

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.",

author = "Sidong Liu and Lei Jing and Weidong Cai and Lingfeng Wen and Stefan Eberl and Fulham, {Michael J.} and Dagan Feng",

year = "2010",

month = dec,

day = "1",

doi = "10.1109/CBMS.2010.6042649",

language = "English",

isbn = "9781424491667",

pages = "243--248",

booktitle = "Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 ; Conference date: 12-10-2010 Through 15-10-2010",

}

Liu, S, Jing, L, Cai, W, Wen, L, Eberl, S, Fulham, MJ & Feng, D 2010, Localized multiscale texture based retrieval of neurological image. in Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010., 6042649, Institute of Electrical and Electronics Engineers (IEEE), pp. 243-248, 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010, Perth, Australia, 12/10/10. https://doi.org/10.1109/CBMS.2010.6042649

Localized multiscale texture based retrieval of neurological image. / Liu, Sidong; Jing, Lei; Cai, Weidong et al.
Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010. Institute of Electrical and Electronics Engineers (IEEE), 2010. p. 243-248 6042649.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Localized multiscale texture based retrieval of neurological image

AU - Liu, Sidong

AU - Jing, Lei

AU - Cai, Weidong

AU - Wen, Lingfeng

AU - Eberl, Stefan

AU - Fulham, Michael J.

AU - Feng, Dagan

PY - 2010/12/1

Y1 - 2010/12/1

N2 - 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.

AB - 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.

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DO - 10.1109/CBMS.2010.6042649

M3 - Conference proceeding contribution

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SN - 9781424491667

SN - 9781424491674

SP - 243

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BT - Proceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010

Y2 - 12 October 2010 through 15 October 2010

ER -

Localized multiscale texture based retrieval of neurological image

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