Stochastic neighbor embedding as a tool for visualizing the encoding capability of magnetic resonance fingerprinting dictionaries.

ABSTRACT:

Objective

To visualize the encoding capability of magnetic resonance fingerprinting (MRF) dictionaries.

Materials and methods

High-dimensional MRF dictionaries were simulated and embedded into a lower-dimensional space using t-distributed stochastic neighbor embedding (t-SNE). The embeddings were visualized via colors as a surrogate for location in low-dimensional space. First, we illustrate this technique on three different MRF sequences. We then compare the resulting embeddings and the color-coded dictionary maps to these obtained with a singular value decomposition (SVD) dimensionality reduction technique. We validate the t-SNE approach with measures based on existing quantitative measures of encoding capability using the Euclidean distance. Finally, we use t-SNE to visua

SUBMITTER: Koolstra K 

PROVIDER: S-EPMC8995272 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature