Discriminative Multi-task Feature Selection for Multi-modality Based AD/MCI Classification

Tingting Ye, Chen Zu, Biao Jie, Dinggang Shen, Daoqiang Zhang

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

2 Citations (Scopus)

Abstract

Recently, multi-task based feature selection methods have been used in multi-modality based classification of Alzheimer's disease (AD) and its prodromal stage, i.e., Mild cognitive impairment (MCI). However, in traditional multi-task feature selection methods, some useful discriminative information among subjects is usually not well mined for further improving the subsequent classification performance. Accordingly, in this paper, we propose a discriminative multi-task feature selection method to select the most discriminative features for multi-modality based classification of AD/MCI. Specifically, for each modality, we traina linear regression model using the corresponding modality of data, and further enforce the group-sparsity regularization on weights of those regression models for joint selection of common features across multiple modalities. Furthermore, we propose a discriminative regularization term based on the intra-class and inter-class Laplacian matrices to better use the discriminative information among subjects. We perform extensive experiments on 202 subjects from the baseline MRI and FDG-PET image data of the Alzheimer's Disease Neuroimaging Initiative (ADNI). The experimental results show that our proposed method improves the classification performance with the comparison to several state-of the-art methods for multi-modality based AD/MCI classification.

Original languageEnglish
Title of host publicationProceedings - 2015 International Workshop on Pattern Recognition in NeuroImaging, PRNI 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages45-48
Number of pages4
ISBN (Print)9781467371452
DOIs
Publication statusPublished - 2015 Sep 16
Externally publishedYes
Event5th International Workshop on Pattern Recognition in NeuroImaging, PRNI 2015 - Stanford, United States
Duration: 2015 Jun 102015 Jun 12

Other

Other5th International Workshop on Pattern Recognition in NeuroImaging, PRNI 2015
CountryUnited States
CityStanford
Period15/6/1015/6/12

Keywords

  • Alzheimer's disease
  • discriminative regularization
  • group-sparsity regularizer
  • multi-modality based classification
  • multi-task feature selection

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Ye, T., Zu, C., Jie, B., Shen, D., & Zhang, D. (2015). Discriminative Multi-task Feature Selection for Multi-modality Based AD/MCI Classification. In Proceedings - 2015 International Workshop on Pattern Recognition in NeuroImaging, PRNI 2015 (pp. 45-48). [7270844] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PRNI.2015.15