Experimental comparisons of sparse dictionary learning and independent component analysis for brain network inference from fMRI data
In this work, we conduct comprehensive comparisons between four variants of independent
component analysis (ICA) methods and three variants of sparse dictionary learning (SDL) …
component analysis (ICA) methods and three variants of sparse dictionary learning (SDL) …
Discovering dynamic functional brain networks via spatial and channel-wise attention
Structured sparse principal components analysis with the TV-elastic net penalty
Principal component analysis (PCA) is an exploratory tool widely used in data analysis to
uncover the dominant patterns of variability within a population. Despite its ability to …
uncover the dominant patterns of variability within a population. Despite its ability to …
Blind image separation based on attentional generative adversarial network
X Sun, J Xu, Y Ma, T Zhao, S Ou, L Peng - Journal of Ambient Intelligence …, 2022 - Springer
Mixing signal separation is an important field of image processing. However, traditional blind
source separation (BSS) algorithms were proposed to solve this task utilizing multiple signal …
source separation (BSS) algorithms were proposed to solve this task utilizing multiple signal …
Map** dynamic spatial patterns of brain function with spatial-wise attention
Objective: Using functional magnetic resonance imaging (fMRI) and deep learning to
discover the spatial pattern of brain function, or functional brain networks (FBNs) has been …
discover the spatial pattern of brain function, or functional brain networks (FBNs) has been …
Blind components processing a novel approach to array signal processing: a research orientation
Blind Components Processing (BCP), a novel approach in processing of data (signal,
image, etc.) components, is introduced as well some applications to information …
image, etc.) components, is introduced as well some applications to information …
Robust subject-wise dictionary learning for fMRI
MU Khalid, BM Albahlal - IEEE Access, 2024 - ieeexplore.ieee.org
This paper presents a robust subject-wise sequential dictionary learning (swsDL) algorithm
named rswsDL for functional magnetic resonance imaging (fMRI) data where the negative …
named rswsDL for functional magnetic resonance imaging (fMRI) data where the negative …
Improving Source Separation for Multi-subject fMRI Data by Incorporating Signal Intensity and Spatiotemporal Basis Expansion
MU Khalid, MM Nauman, PMIB Pg Hj Petra… - Proceedings of the 2024 …, 2024 - dl.acm.org
Recently, a sparse spatiotemporal blind source separation (ssBSS) algorithm was proposed
to perform functional magnetic resonance imaging (fMRI) data analysis as a potential …
to perform functional magnetic resonance imaging (fMRI) data analysis as a potential …