Name
Title | ||
|---|---|---|
Discriminative Multi-task Feature Selection for Multi-modality Based AD/MCI Classification |
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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/PRNI.2015.15 | 2015 International Workshop on Pattern Recognition in NeuroImaging |
Keywords | Field | DocType |
Alzheimer's disease,multi-task feature selection,multi-modality based classification,discriminative regularization,group-sparsity regularizer | Pattern recognition,Feature selection,Multiple modalities,Regression analysis,Psychology,Regularization (mathematics),Artificial intelligence,Neuroimaging,Discriminative model,Machine learning,Cognitive impairment,Linear regression | Conference |
Citations | PageRank | References |
1 | 0.34 | 9 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tingting Ye | 1 | 1 | 0.34 |
| Chen Zu | 2 | 28 | 5.53 |
| Biao Jie | 3 | 91 | 16.95 |
| Dinggang Shen | 4 | 7837 | 611.27 |
| Daoqiang Zhang | 5 | 2862 | 165.29 |