Accelerating MR Parameter Mapping Using Nonlinear Compressive Manifold Learning and Regularized Pre-Imaging.
Yihang ZhouHaifeng WangYuanyuan LiuDong LiangLeslie YingPublished in: IEEE Trans. Biomed. Eng. (2022)
Keyphrases
- manifold learning
- nonlinear manifold learning
- nonlinear manifold
- low dimensional
- principal curves
- low dimensional manifolds
- dimensionality reduction
- feature mapping
- high dimensional feature space
- nonlinear dimensionality reduction
- manifold embedding
- embedding space
- semi supervised
- high dimensional
- image processing
- sparse representation
- laplacian eigenmaps
- high resolution
- subspace learning
- dimension reduction
- latent space
- diffusion maps
- high dimensional data
- feature extraction
- manifold learning algorithm
- head pose estimation
- random projections
- image data
- underlying manifold
- parameter space
- image registration
- feature space
- manifold structure
- locally linear embedding
- input space
- medical images
- medical imaging
- feature selection
- data points
- intrinsic dimensionality
- least squares
- principal component analysis
- riemannian manifolds