Canonical feature selection for joint regression and multi-class identification in Alzheimer's disease diagnosis.
Fusing information from different imaging modalities is crucial for more accurate identification of the brain state because imaging data of different modalities can provide complementary perspectives on the complex nature of brain disorders. However, most existing fusion methods often extract featur...
| Published in: | Brain Imaging & Behavior Vol. 10; no. 3; pp. 818 - 829 |
|---|---|
| Main Authors: | , , , |
| Format: | research Journal Article |
| Published: |
Springer Nature
Sep2016
|
| Online Access: | View this record in EBSCOhost |