[HTML][HTML] Concurrent white matter bundles and grey matter networks using independent component analysis
J O'Muircheartaigh, S Jbabdi - NeuroImage, 2018 - Elsevier
Developments in non-invasive diffusion MRI tractography techniques have permitted the
investigation of both the anatomy of white matter pathways connecting grey matter regions …
investigation of both the anatomy of white matter pathways connecting grey matter regions …
A review on mr based human brain parcellation methods
Brain parcellations play a ubiquitous role in the analysis of magnetic resonance imaging
(MRI) datasets. Over 100 years of research has been conducted in pursuit of an ideal brain …
(MRI) datasets. Over 100 years of research has been conducted in pursuit of an ideal brain …
Group-wise parcellation of the cortex through multi-scale spectral clustering
The delineation of functionally and structurally distinct regions as well as their connectivity
can provide key knowledge towards understanding the brain's behaviour and function …
can provide key knowledge towards understanding the brain's behaviour and function …
[HTML][HTML] From coarse to fine-grained parcellation of the cortical surface using a fiber-bundle atlas
In this article, we present a hybrid method to create fine-grained parcellations of the cortical
surface, from a coarse-grained parcellation according to an anatomical atlas, based on …
surface, from a coarse-grained parcellation according to an anatomical atlas, based on …
[HTML][HTML] Learning cortical parcellations using graph neural networks
KM Eschenburg, TJ Grabowski… - Frontiers in neuroscience, 2021 - frontiersin.org
Deep learning has been applied to magnetic resonance imaging (MRI) for a variety of
purposes, ranging from the acceleration of image acquisition and image denoising to tissue …
purposes, ranging from the acceleration of image acquisition and image denoising to tissue …
Groupwise structural parcellation of the whole cortex: A logistic random effects model based approach
Current theories hold that brain function is highly related to long-range physical connections
through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise …
through axonal bundles, namely extrinsic connectivity. However, obtaining a groupwise …
Group-wise cortical parcellation based on structural connectivity and hierarchical clustering
This paper presents a new cortical parcellation method based on group-wise connectivity
and hierarchical clustering. A preliminary sub-parcellation is performed using intra-subject …
and hierarchical clustering. A preliminary sub-parcellation is performed using intra-subject …
Automated connectivity-based groupwise cortical atlas generation: Application to data of neurosurgical patients with brain tumors for cortical parcellation prediction
This work presents an initial exploration of joint cortical surface and diffusion MRI analysis
for neurosurgical patient data. We propose a groupwise cortical modeling strategy that …
for neurosurgical patient data. We propose a groupwise cortical modeling strategy that …
Network alignment and similarity reveal atlas-based topological differences in structural connectomes
The interactions between different brain regions can be modeled as a graph, called
connectome, whose nodes correspond to parcels from a predefined brain atlas. The edges …
connectome, whose nodes correspond to parcels from a predefined brain atlas. The edges …
GraMPa: Graph-based multi-modal parcellation of the cortex using fusion moves
Parcellating the brain into a set of distinct subregions is an essential step for building and
studying brain connectivity networks. Connectivity driven parcellation is a natural approach …
studying brain connectivity networks. Connectivity driven parcellation is a natural approach …