58 citations · 154 across the 35 of their papers we have counts for
5 papers · 1 filter
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography
Haolin He, Ce Zhu, Le Zhang +9
The amygdala plays a vital role in emotional processing and exhibits structural diversity that necessitates fine-scale parcellation for a comprehensive understanding of its anatomi…
TractCloud: Registration-free tractography parcellation with a novel local-global streamline point cloud representation
Tengfei Xue, Yuqian Chen, Chaoyi Zhang +6
Diffusion MRI tractography parcellation classifies streamlines into anatomical fiber tracts to enable quantification and visualization for clinical and scientific applications. Cur…
TractGeoNet: A geometric deep learning framework for pointwise analysis of tract microstructure to predict language assessment performance
Yuqian Chen, Leo R. Zekelman, Chaoyi Zhang +8
We propose a geometric deep-learning-based framework, TractGeoNet, for performing regression using diffusion magnetic resonance imaging (dMRI) tractography and associated pointwise…
Fiber Tract Shape Measures Inform Prediction of Non-Imaging Phenotypes
Wan Liu, Yuqian Chen, Chuyang Ye +5
Neuroimaging measures of the brain's white matter connections can enable the prediction of non-imaging phenotypes, such as demographic and cognitive measures. Existing works have i…
TractGraphCNN: anatomically informed graph CNN for classification using diffusion MRI tractography
Yuqian Chen, Fan Zhang, Leo R. Zekelman +7
The structure and variability of the brain's connections can be investigated via prediction of non-imaging phenotypes using neural networks. However, known neuroanatomical relation…