Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation …
Diffusion MRI tractography is an advanced imaging technique that enables in vivo map**
of the brain's white matter connections. White matter parcellation classifies tractography …
of the brain's white matter connections. White matter parcellation classifies tractography …
Supwma: consistent and efficient tractography parcellation of superficial white matter with deep learning
White matter parcellation classifies tractography streamlines into clusters or anatomically
meaningful tracts to enable quantification and visualization. Most parcellation methods focus …
meaningful tracts to enable quantification and visualization. Most parcellation methods focus …
PointNeuron: 3D Neuron Reconstruction via Geometry and Topology Learning of Point Clouds
Digital neuron reconstruction from 3D microscopy images is an essential technique for
investigating brain connectomics and neuron morphology. Existing reconstruction …
investigating brain connectomics and neuron morphology. Existing reconstruction …
White matter tracts are point clouds: neuropsychological score prediction and critical region localization via geometric deep learning
White matter tract microstructure has been shown to influence neuropsychological scores of
cognitive performance. However, prediction of these scores from white matter tract data has …
cognitive performance. However, prediction of these scores from white matter tract data has …
[HTML][HTML] Deep fiber clustering: anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation
White matter fiber clustering is an important strategy for white matter parcellation, which
enables quantitative analysis of brain connections in health and disease. In combination …
enables quantitative analysis of brain connections in health and disease. In combination …
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
We propose a geometric deep-learning-based framework, TractGeoNet, for performing
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …
regression using diffusion magnetic resonance imaging (dMRI) tractography and associated …
TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Classification from Diffusion MRI Tractography
The relationship between brain connections and non-imaging phenotypes is increasingly
studied using deep neural networks. However, the local and global properties of the brain's …
studied using deep neural networks. However, the local and global properties of the brain's …
TractCloud: Registration-free tractography parcellation with a novel local-global streamline point cloud representation
Diffusion MRI tractography parcellation classifies streamlines into anatomical fiber tracts to
enable quantification and visualization for clinical and scientific applications. Current …
enable quantification and visualization for clinical and scientific applications. Current …
[HTML][HTML] Randomized iterative spherical‐deconvolution informed tractogram filtering
Tractography has become an indispensable part of brain connectivity studies. However, it is
currently facing problems with reliability. In particular, a substantial amount of nerve fiber …
currently facing problems with reliability. In particular, a substantial amount of nerve fiber …
TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography
The relationship between brain connections and non-imaging phenotypes is increasingly
studied using deep neural networks. However, the local and global properties of the brain's …
studied using deep neural networks. However, the local and global properties of the brain's …