Discriminative group sparse representation for mild cognitive impairment classification

Heung-Il Suk, Chong Yaw Wee, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

21 Citations (Scopus)

Abstract

Witnessed by recent studies, functional connectivity is a useful tool in extracting brain network features and finding biomarkers for brain disease diagnosis. It still remains, however, challenging for the estimation of a functional connectivity from fMRI due to the high dimensional nature. In order to tackle this problem, we utilize a group sparse representation along with a structural equation model. Unlike the conventional group sparse representation, we devise a novel supervised discriminative group sparse representation by penalizing a large within-class variance and a small between-class variance of features. Thanks to the devised penalization term, we can learn connectivity coefficients that are similar within the same class and distinct between classes, thus helping enhance the diagnostic accuracy. In our experiments on the resting-state fMRI data of 37 subjects (12 mild cognitive impairment patients; 25 healthy normal controls) with a cross-validation technique, we demonstrated the validity and effectiveness of the proposed method, showing the best diagnostic accuracy of 89.19% and the sensitivity of 0.9167.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages131-138
Number of pages8
Volume8184 LNCS
ISBN (Print)9783319022666
DOIs
Publication statusPublished - 2013 Jan 1
Externally publishedYes
Event4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: 2013 Sep 222013 Sep 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8184 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
CountryJapan
CityNagoya
Period13/9/2213/9/22

Fingerprint

Sparse Representation
Brain
Diagnostic Accuracy
Connectivity
Functional Magnetic Resonance Imaging
Biomarkers
Structural Equation Model
Penalization
Cross-validation
High-dimensional
Experiments
Distinct
Class
Magnetic Resonance Imaging
Coefficient
Term
Experiment

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Suk, H-I., Wee, C. Y., & Shen, D. (2013). Discriminative group sparse representation for mild cognitive impairment classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8184 LNCS, pp. 131-138). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8184 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-02267-3_17

Discriminative group sparse representation for mild cognitive impairment classification. / Suk, Heung-Il; Wee, Chong Yaw; Shen, Dinggang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8184 LNCS Springer Verlag, 2013. p. 131-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8184 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suk, H-I, Wee, CY & Shen, D 2013, Discriminative group sparse representation for mild cognitive impairment classification. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 8184 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8184 LNCS, Springer Verlag, pp. 131-138, 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, Nagoya, Japan, 13/9/22. https://doi.org/10.1007/978-3-319-02267-3_17
Suk H-I, Wee CY, Shen D. Discriminative group sparse representation for mild cognitive impairment classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8184 LNCS. Springer Verlag. 2013. p. 131-138. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-02267-3_17
Suk, Heung-Il ; Wee, Chong Yaw ; Shen, Dinggang. / Discriminative group sparse representation for mild cognitive impairment classification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8184 LNCS Springer Verlag, 2013. pp. 131-138 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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