Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso

Xiangyu Chen; Yanwu Xu; Shuicheng Yan; Tat Seng Chua; Damon Wing Kee Wong; Tien Yin Wong; Jiang Liu

doi:10.1007/978-3-319-24571-3_2

Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso

Xiangyu Chen, Yanwu Xu, Shuicheng Yan, Tat Seng Chua, Damon Wing Kee Wong, Tien Yin Wong, Jiang Liu

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

2 Citations (Scopus)

Abstract

Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three leading ocular diseases worldwide. Visual features extracted from retinal fundus images have been increasingly used for detecting these three diseases. In this paper, we present a discriminative feature selection model based on multi-task learning, which imposes the exclusive group lasso regularization for competitive sparse feature selection and the graph Laplacian regularization to embed the correlations among multiple diseases. Moreover, this multi-task linear discriminative model is able to simultaneously select sparse features and detect multiple ocular diseases. Extensive experiments are conducted to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
Editors	Joachim Hornegger, Alejandro F. Frangi, William M. Wells, Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, Nassir Navab, William M. Wells, William M. Wells, Alejandro F. Frangi, Joachim Hornegger, Nassir Navab
Publisher	Springer Verlag
Pages	11-19
Number of pages	9
ISBN (Print)	9783319245706, 9783319245706, 9783319245706
DOIs	https://doi.org/10.1007/978-3-319-24571-3_2
Publication status	Published - 2015
Externally published	Yes
Event	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany Duration: 5 Oct 2015 → 9 Oct 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9350
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/Territory	Germany
City	Munich
Period	5/10/15 → 9/10/15

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-319-24571-3_2

Cite this

Chen, X., Xu, Y., Yan, S., Chua, T. S., Wong, D. W. K., Wong, T. Y., & Liu, J. (2015). Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso. In J. Hornegger, A. F. Frangi, W. M. Wells, A. F. Frangi, N. Navab, J. Hornegger, N. Navab, W. M. Wells, W. M. Wells, A. F. Frangi, J. Hornegger, & N. Navab (Eds.), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings (pp. 11-19). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9350). Springer Verlag. https://doi.org/10.1007/978-3-319-24571-3_2

Chen, Xiangyu ; Xu, Yanwu ; Yan, Shuicheng et al. / Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso. Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. editor / Joachim Hornegger ; Alejandro F. Frangi ; William M. Wells ; Alejandro F. Frangi ; Nassir Navab ; Joachim Hornegger ; Nassir Navab ; William M. Wells ; William M. Wells ; Alejandro F. Frangi ; Joachim Hornegger ; Nassir Navab. Springer Verlag, 2015. pp. 11-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{dff8f1ec4d3147269b64f32aef988f14,

title = "Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso",

abstract = "Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three leading ocular diseases worldwide. Visual features extracted from retinal fundus images have been increasingly used for detecting these three diseases. In this paper, we present a discriminative feature selection model based on multi-task learning, which imposes the exclusive group lasso regularization for competitive sparse feature selection and the graph Laplacian regularization to embed the correlations among multiple diseases. Moreover, this multi-task linear discriminative model is able to simultaneously select sparse features and detect multiple ocular diseases. Extensive experiments are conducted to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.",

author = "Xiangyu Chen and Yanwu Xu and Shuicheng Yan and Chua, {Tat Seng} and Wong, {Damon Wing Kee} and Wong, {Tien Yin} and Jiang Liu",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 ; Conference date: 05-10-2015 Through 09-10-2015",

year = "2015",

doi = "10.1007/978-3-319-24571-3_2",

language = "English",

isbn = "9783319245706",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "11--19",

editor = "Joachim Hornegger and Frangi, {Alejandro F.} and Wells, {William M.} and Frangi, {Alejandro F.} and Nassir Navab and Joachim Hornegger and Nassir Navab and Wells, {William M.} and Wells, {William M.} and Frangi, {Alejandro F.} and Joachim Hornegger and Nassir Navab",

booktitle = "Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings",

address = "Germany",

}

Chen, X, Xu, Y, Yan, S, Chua, TS, Wong, DWK, Wong, TY & Liu, J 2015, Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso. in J Hornegger, AF Frangi, WM Wells, AF Frangi, N Navab, J Hornegger, N Navab, WM Wells, WM Wells, AF Frangi, J Hornegger & N Navab (eds), Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9350, Springer Verlag, pp. 11-19, 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015, Munich, Germany, 5/10/15. https://doi.org/10.1007/978-3-319-24571-3_2

Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso. / Chen, Xiangyu; Xu, Yanwu; Yan, Shuicheng et al.
Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. ed. / Joachim Hornegger; Alejandro F. Frangi; William M. Wells; Alejandro F. Frangi; Nassir Navab; Joachim Hornegger; Nassir Navab; William M. Wells; William M. Wells; Alejandro F. Frangi; Joachim Hornegger; Nassir Navab. Springer Verlag, 2015. p. 11-19 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9350).

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

TY - GEN

T1 - Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso

AU - Chen, Xiangyu

AU - Xu, Yanwu

AU - Yan, Shuicheng

AU - Chua, Tat Seng

AU - Wong, Damon Wing Kee

AU - Wong, Tien Yin

AU - Liu, Jiang

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three leading ocular diseases worldwide. Visual features extracted from retinal fundus images have been increasingly used for detecting these three diseases. In this paper, we present a discriminative feature selection model based on multi-task learning, which imposes the exclusive group lasso regularization for competitive sparse feature selection and the graph Laplacian regularization to embed the correlations among multiple diseases. Moreover, this multi-task linear discriminative model is able to simultaneously select sparse features and detect multiple ocular diseases. Extensive experiments are conducted to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.

AB - Glaucoma, Pathological Myopia (PM), and Age-related Macular Degeneration (AMD) are three leading ocular diseases worldwide. Visual features extracted from retinal fundus images have been increasingly used for detecting these three diseases. In this paper, we present a discriminative feature selection model based on multi-task learning, which imposes the exclusive group lasso regularization for competitive sparse feature selection and the graph Laplacian regularization to embed the correlations among multiple diseases. Moreover, this multi-task linear discriminative model is able to simultaneously select sparse features and detect multiple ocular diseases. Extensive experiments are conducted to validate the proposed framework on the SiMES dataset. From the Area Under Curve (AUC) results in multiple ocular diseases classification, our method is shown to outperform the state-of-the-art algorithms.

UR - http://www.scopus.com/inward/record.url?scp=84951093680&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-24571-3_2

DO - 10.1007/978-3-319-24571-3_2

M3 - Conference contribution

AN - SCOPUS:84951093680

SN - 9783319245706

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 11

EP - 19

BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings

A2 - Hornegger, Joachim

A2 - Frangi, Alejandro F.

A2 - Wells, William M.

A2 - Frangi, Alejandro F.

A2 - Navab, Nassir

A2 - Hornegger, Joachim

A2 - Navab, Nassir

A2 - Wells, William M.

A2 - Frangi, Alejandro F.

A2 - Hornegger, Joachim

A2 - Navab, Nassir

PB - Springer Verlag

T2 - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015

Y2 - 5 October 2015 through 9 October 2015

ER -

Chen X, Xu Y, Yan S, Chua TS, Wong DWK, Wong TY et al. Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso. In Hornegger J, Frangi AF, Wells WM, Frangi AF, Navab N, Hornegger J, Navab N, Wells WM, Wells WM, Frangi AF, Hornegger J, Navab N, editors, Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings. Springer Verlag. 2015. p. 11-19. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-24571-3_2

Discriminative feature selection for multiple ocular diseases classification by sparse induced graph regularized group lasso

Abstract

Publication series

Conference

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this