High-dimensional MRI data analysis using a large-scale manifold learning approach.
Loc TranDebrup BanerjeeJihong WangAshok J. KumarFrederic D. McKenzieYaohang LiJiang LiPublished in: Mach. Vis. Appl. (2013)
Keyphrases
- manifold learning
- high dimensional
- data analysis
- high dimensional data
- low dimensional
- dimensionality reduction
- nonlinear dimensionality reduction
- dimension reduction
- laplacian eigenmaps
- high dimensionality
- diffusion maps
- subspace learning
- low dimensional manifolds
- similarity search
- head pose estimation
- manifold structure
- semi supervised
- data points
- medical images
- input space
- lower dimensional
- nearest neighbor
- high dimensional spaces
- feature extraction
- parameter space
- high resolution
- feature space
- locally linear embedding
- embedding space
- data sets
- nonlinear manifold
- high dimension
- cluster analysis
- multi dimensional
- data mining
- neural network