[HTML][HTML] SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data
QH Lin, YW Niu, J Sui, WD Zhao, C Zhuo… - Medical Image …, 2022 - Elsevier
Convolutional neural networks (CNNs) have shown promising results in classifying
individuals with mental disorders such as schizophrenia using resting-state fMRI data …
individuals with mental disorders such as schizophrenia using resting-state fMRI data …
The future of susceptibility contrast for assessment of anatomy and function
JR Reichenbach - Neuroimage, 2012 - Elsevier
The magnetic properties of tissues affect MR images and differences in magnetic
susceptibility can be utilized to provide impressive image contrast. Specifically, phase …
susceptibility can be utilized to provide impressive image contrast. Specifically, phase …
Toward online reconstruction of quantitative susceptibility maps: superfast dipole inversion
Magnetic susceptibility is an intrinsic tissue property that recently became measureable in
vivo by a magnetic‐resonance based technique called quantitative susceptibility map** …
vivo by a magnetic‐resonance based technique called quantitative susceptibility map** …
Functional quantitative susceptibility map** (fQSM)
Blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI)
is a powerful technique, typically based on the statistical analysis of the magnitude …
is a powerful technique, typically based on the statistical analysis of the magnitude …
A multiple kernel learning approach to perform classification of groups from complex-valued fMRI data analysis: application to schizophrenia
FMRI data are acquired as complex-valued spatiotemporal images. Despite the fact that
several studies have identified the presence of novel information in the phase images, they …
several studies have identified the presence of novel information in the phase images, they …
[HTML][HTML] Complex-valued time series modeling for improved activation detection in fMRI studies
DW Adrian, R Maitra, DB Rowe - The annals of applied statistics, 2018 - ncbi.nlm.nih.gov
A complex-valued data-based model with pth order autoregressive errors and general
real/imaginary error covariance structure is proposed as an alternative to the commonly …
real/imaginary error covariance structure is proposed as an alternative to the commonly …
Changes in fMRI magnitude data and phase data observed in block-design and event-related tasks
Functional magnetic resonance imaging (fMRI) data are acquired as a complex image pair
including magnitude and phase information. The vast majority of fMRI experiments do not …
including magnitude and phase information. The vast majority of fMRI experiments do not …
Application of independent component analysis with adaptive density model to complex-valued fMRI data
Independent component analysis (ICA) has proven quite useful for the analysis of real world
datasets such as functional resonance magnetic imaging (fMRI) data, where the underlying …
datasets such as functional resonance magnetic imaging (fMRI) data, where the underlying …
Model order effects on ICA of resting-state complex-valued fMRI data: application to schizophrenia
Background Component splitting at higher model orders is a widely accepted finding for
independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) …
independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) …
De-noising, phase ambiguity correction and visualization techniques for complex-valued ICA of group fMRI data
Analysis of functional magnetic resonance imaging (fMRI) data in its native, complex form
has been shown to increase the sensitivity and specificity both for data-driven techniques …
has been shown to increase the sensitivity and specificity both for data-driven techniques …