The exponential growth of fMRI big data offers researchers an unprecedented opportunity to explore functional brain networks. However, this opportunity has not been fully explored yet due to the lack of effective and efficient tools for handling such fMRI big data. One major challenge is that computing capabilities still lag behind the growth of large-scale fMRI databases, e.g., it takes many days to perform dictionary learning and sparse coding of whole-brain fMRI data for an fMRI database of average size. Therefore, how to reduce the data size but without losing important information becomes a more and more pressing issue. To address this problem, we propose a signal sampling approach for significant fMRI data reduction before performing ...
Developments in technology have enabled scientists to study brain function in an unprecedented way. ...
International audienceSpontaneous brain activity reveals mechanisms of brain function and dysfunctio...
In this paper, we introduce a novel methodology for the analysis of task-related fMRI data. In parti...
By finding broader temporal and spatial patterns of brain activity, dictionary learning and sparse c...
International audienceWe present a method for fast resting-state fMRI spatial decompositions of very...
In this paper, the task-related fMRI problem is treated in its matrix factorization form, focusing o...
© 2019 Asif IqbalFunctional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging techniq...
Statistical parametric mapping (SPM) of functional mag-netic resonance imaging (fMRI) uses a canonic...
Abstract—This paper focuses on detecting activated voxels in fMRI data by exploiting the sparsity of...
Data driven analysis methods such as independent component analysis (ICA) have proven to be well sui...
BackgroundBrain networks in fMRI are typically identified using spatial independent component analys...
A principal component analysis (PCA) based dictionary initialization approach accompanied by a compu...
Functional neuroimaging can measure the brain’s response to an external stimulus. It is used to perf...
Thanks to the advent of functional brain-imaging technologies, cognitive neuroscience is accumulatin...
International audienceFluctuations in brain on-going activity can be used to reveal its intrinsic fu...
Developments in technology have enabled scientists to study brain function in an unprecedented way. ...
International audienceSpontaneous brain activity reveals mechanisms of brain function and dysfunctio...
In this paper, we introduce a novel methodology for the analysis of task-related fMRI data. In parti...
By finding broader temporal and spatial patterns of brain activity, dictionary learning and sparse c...
International audienceWe present a method for fast resting-state fMRI spatial decompositions of very...
In this paper, the task-related fMRI problem is treated in its matrix factorization form, focusing o...
© 2019 Asif IqbalFunctional Magnetic Resonance Imaging (fMRI) is a non-invasive neuroimaging techniq...
Statistical parametric mapping (SPM) of functional mag-netic resonance imaging (fMRI) uses a canonic...
Abstract—This paper focuses on detecting activated voxels in fMRI data by exploiting the sparsity of...
Data driven analysis methods such as independent component analysis (ICA) have proven to be well sui...
BackgroundBrain networks in fMRI are typically identified using spatial independent component analys...
A principal component analysis (PCA) based dictionary initialization approach accompanied by a compu...
Functional neuroimaging can measure the brain’s response to an external stimulus. It is used to perf...
Thanks to the advent of functional brain-imaging technologies, cognitive neuroscience is accumulatin...
International audienceFluctuations in brain on-going activity can be used to reveal its intrinsic fu...
Developments in technology have enabled scientists to study brain function in an unprecedented way. ...
International audienceSpontaneous brain activity reveals mechanisms of brain function and dysfunctio...
In this paper, we introduce a novel methodology for the analysis of task-related fMRI data. In parti...