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

22 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 publicationMachine Learning in Medical Imaging - 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Proceedings
PublisherSpringer Verlag
Pages131-138
Number of pages8
ISBN (Print)9783319022666
DOIs
Publication statusPublished - 2013
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)0302-9743
ISSN (Electronic)1611-3349

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

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Suk, H. I., Wee, C. Y., & Shen, D. (2013). Discriminative group sparse representation for mild cognitive impairment classification. In Machine Learning in Medical Imaging - 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Proceedings (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