7 citations · 8 across the 5 of their papers we have counts for
6 papers
dMRI-F: A Foundation Model for Generalizable Diffusion MRI Analysis from Sparse Acquisitions
Xi Zhu, Yijie Li, Xiaofan Wang +4
Diffusion MRI (dMRI) probes water diffusion within the brain, providing unique information about tissue microstructure and white matter connectivity. High-quality dMRI enables adva…
LGLG-WPCA: An Effective Texture-based Method for Face Recognition
Chaorong Li, Huang Wei, Huafu Chen
In this paper, we proposed an effective face feature extraction method by Learning Gabor Log-Euclidean Gaussian with Whitening Principal Component Analysis (WPCA), called LGLG-WPCA…
Randomized Structural Sparsity based Support Identification with Applications to Locating Activated or Discriminative Brain Areas: A Multi-center Reproducibility Study
Yilun Wang, Sheng Zhang, Junjie Zheng +2
In this paper, we focus on how to locate the relevant or discriminative brain regions related with external stimulus or certain mental decease, which is also called support identif…
A Novel Approach for Stable Selection of Informative Redundant Features from High Dimensional fMRI Data
Yilun Wang, Zhiqiang Li, Yifeng Wang +4
Feature selection is among the most important components because it not only helps enhance the classification accuracy, but also or even more important provides potential biomarker…
Randomized Structural Sparsity via Constrained Block Subsampling for Improved Sensitivity of Discriminative Voxel Identification
Yilun Wang, Junjie Zheng, Sheng Zhang +2
In this paper, we consider voxel selection for functional Magnetic Resonance Imaging (fMRI) brain data with the aim of finding a more complete set of probably correlated discrimina…
A blind deconvolution approach to recover effective connectivity brain networks from resting state fMRI data
G. Wu, W. Liao, S. Stramaglia +3
A great improvement to the insight on brain function that we can get from fMRI data can come from effective connectivity analysis, in which the flow of information between even rem…