Name
Abstract | ||
|---|---|---|
Learning low dimensional embedding spaces (manifolds) for efficient feature representation is crucial for complex and high dimensional input spaces. Functional magnetic resonance imaging (fMRI) produces high dimensional input data and with a less then ideal number of labeled samples for a classification task. In this study, we explore deep learning methods for fMRI classification tasks in order to reduce dimensions of feature space, along with improving classification performance for brain decoding. We employ sparse autoencoders for unsupervised feature learning, leveraging unlabeled fMRI data to learn efficient, non-linear representations as the building blocks of a deep learning architecture by stacking them. Proposed method is tested on a memory encoding/retrieval experiment with ten classes. The results support the efficiency compared to the baseline multi-voxel pattern analysis techniques. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/ICIP.2014.7025563 | Image Processing |
Keywords | Field | DocType |
biomedical MRI,brain,decoding,feature extraction,image classification,medical image processing,neurophysiology,unsupervised learning,baseline multi-voxel pattern analysis techniques,brain decoding,complex input spaces,deep learning architecture,deep learning methods,efficient feature representation,fMRI classification tasks,feature space dimension,functional magnetic resonance imaging,high dimensional input data,high dimensional input spaces,low dimensional embedding spaces,manifolds,memory encoding,memory retrieval,nonlinear representations,sample classification,sparse autoencoders,unlabeled fMRI data,unsupervised feature learning,Deep Learning,MVPA,Stacked Autoencoders,brain state decoding,fMRI | Computer science,Deep belief network,Artificial intelligence,Deep learning,Manifold,Computer vision,Feature vector,Embedding,Pattern recognition,Decoding methods,Machine learning,Feature learning,Encoding (memory) | Conference |
ISSN | Citations | PageRank |
1522-4880 | 1 | 0.36 |
References | Authors | |
20 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Orhan Firat | 1 | 281 | 29.13 |
| Like Oztekin | 2 | 1 | 0.36 |
| Yarman Vural, F.T. | 3 | 73 | 6.17 |