Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval

Sidong Liu; Weidong Cai; Lingfeng Wen; David Dagan Feng

doi:10.1109/ICIP.2012.6467093

Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval

Sidong Liu^*, Weidong Cai, Lingfeng Wen, David Dagan Feng

^*Corresponding author for this work

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

11 Citations (Scopus)

Abstract

Accurate neuroimaging feature extraction is essential for effective content-based management of the large neuroimaging databases, as well as achieving improved diagnosis. In this paper, we presented a multiscale and multi-orientation neuroimaging feature extraction algorithm with degenerative patterns for content-based 3D neuroimaging analysis and retrieval, based on the localized 3D Gabor wavelets. Our proposed approach was evaluated with 209 3D clinical neurological imaging studies and compared with the 3D discrete curvelet transform based method and the 3D spatial grey level co-occurrence matrices based method. The preliminary results suggested that our algorithm could support more reliable 3D neuroimaging retrieval.

Original language	English
Title of host publication	2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1249-1252
Number of pages	4
ISBN (Electronic)	9781467325325
ISBN (Print)	9781467325332, 9781467325349
DOIs	https://doi.org/10.1109/ICIP.2012.6467093
Publication status	Published - 1 Dec 2012
Externally published	Yes
Event	2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States Duration: 30 Sept 2012 → 3 Oct 2012

Conference

Conference	2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/Territory	United States
City	Lake Buena Vista, FL
Period	30/09/12 → 3/10/12

Keywords

feature extraction
localized 3D Gabor wavelets
neuroimaging retrieval

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10.1109/ICIP.2012.6467093

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Liu, S., Cai, W., Wen, L., & Feng, D. D. (2012). Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval. In 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings (pp. 1249-1252). Article 6467093 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICIP.2012.6467093

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title = "Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval",

abstract = "Accurate neuroimaging feature extraction is essential for effective content-based management of the large neuroimaging databases, as well as achieving improved diagnosis. In this paper, we presented a multiscale and multi-orientation neuroimaging feature extraction algorithm with degenerative patterns for content-based 3D neuroimaging analysis and retrieval, based on the localized 3D Gabor wavelets. Our proposed approach was evaluated with 209 3D clinical neurological imaging studies and compared with the 3D discrete curvelet transform based method and the 3D spatial grey level co-occurrence matrices based method. The preliminary results suggested that our algorithm could support more reliable 3D neuroimaging retrieval.",

keywords = "feature extraction, localized 3D Gabor wavelets, neuroimaging retrieval",

author = "Sidong Liu and Weidong Cai and Lingfeng Wen and Feng, {David Dagan}",

year = "2012",

month = dec,

day = "1",

doi = "10.1109/ICIP.2012.6467093",

language = "English",

isbn = "9781467325332",

pages = "1249--1252",

booktitle = "2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings",

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

address = "United States",

note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",

}

Liu, S, Cai, W, Wen, L & Feng, DD 2012, Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval. in 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings., 6467093, Institute of Electrical and Electronics Engineers (IEEE), pp. 1249-1252, 2012 19th IEEE International Conference on Image Processing, ICIP 2012, Lake Buena Vista, FL, United States, 30/09/12. https://doi.org/10.1109/ICIP.2012.6467093

Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval. / Liu, Sidong; Cai, Weidong; Wen, Lingfeng et al.
2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 2012. p. 1249-1252 6467093.

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

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T1 - Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval

AU - Liu, Sidong

AU - Cai, Weidong

AU - Wen, Lingfeng

AU - Feng, David Dagan

PY - 2012/12/1

Y1 - 2012/12/1

N2 - Accurate neuroimaging feature extraction is essential for effective content-based management of the large neuroimaging databases, as well as achieving improved diagnosis. In this paper, we presented a multiscale and multi-orientation neuroimaging feature extraction algorithm with degenerative patterns for content-based 3D neuroimaging analysis and retrieval, based on the localized 3D Gabor wavelets. Our proposed approach was evaluated with 209 3D clinical neurological imaging studies and compared with the 3D discrete curvelet transform based method and the 3D spatial grey level co-occurrence matrices based method. The preliminary results suggested that our algorithm could support more reliable 3D neuroimaging retrieval.

AB - Accurate neuroimaging feature extraction is essential for effective content-based management of the large neuroimaging databases, as well as achieving improved diagnosis. In this paper, we presented a multiscale and multi-orientation neuroimaging feature extraction algorithm with degenerative patterns for content-based 3D neuroimaging analysis and retrieval, based on the localized 3D Gabor wavelets. Our proposed approach was evaluated with 209 3D clinical neurological imaging studies and compared with the 3D discrete curvelet transform based method and the 3D spatial grey level co-occurrence matrices based method. The preliminary results suggested that our algorithm could support more reliable 3D neuroimaging retrieval.

KW - feature extraction

KW - localized 3D Gabor wavelets

KW - neuroimaging retrieval

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U2 - 10.1109/ICIP.2012.6467093

DO - 10.1109/ICIP.2012.6467093

M3 - Conference proceeding contribution

AN - SCOPUS:84875834406

SN - 9781467325332

SN - 9781467325349

SP - 1249

EP - 1252

BT - 2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2012 19th IEEE International Conference on Image Processing, ICIP 2012

Y2 - 30 September 2012 through 3 October 2012

ER -

Multiscale and multiorientation feature extraction with degenerative patterns for 3D neuroimaging retrieval

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