58 citations · 122 across the 15 of their papers we have counts for
16 papers
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…
Reconstructing the somatotopic organization of the corticospinal tract remains a challenge for modern tractography methods
Jianzhong He, Fan Zhang, Yiang Pan +8
The corticospinal tract (CST) is a critically important white matter fiber tract in the human brain that enables control of voluntary movements of the body. Diffusion MRI tractogra…
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…
DeepRGVP: A Novel Microstructure-Informed Supervised Contrastive Learning Framework for Automated Identification Of The Retinogeniculate Pathway Using dMRI Tractography
Sipei Li, Jianzhong He, Tengfei Xue +13
The retinogeniculate pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus. Identification and visualization of the RGVP a…
Tractography-Based Parcellation of Cerebellar Dentate Nuclei via a Deep Nonnegative Matrix Factorization Clustering Method
Xiao Xu, Yuqian Chen, Leo Zekelman +4
As the largest human cerebellar nucleus, the dentate nucleus (DN) functions significantly in the communication between the cerebellum and the rest of the brain. Structural connecti…
Age Prediction Performance Varies Across Deep, Superficial, and Cerebellar White Matter Connections
Yuxiang Wei, Tengfei Xue, Yogesh Rathi +3
The brain's white matter (WM) undergoes developmental and degenerative processes during the human lifespan. To investigate the relationship between WM anatomical regions and age, w…
TractoSCR: A Novel Supervised Contrastive Regression Framework for Prediction of Neurocognitive Measures Using Multi-Site Harmonized Diffusion MRI Tractography
Tengfei Xue, Fan Zhang, Leo R. Zekelman +9
Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain's structure relates to cognitive function. However, the accuracy of prediction using…
TractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers
Fan Zhang, Tengfei Xue, Weidong Cai +3
Diffusion MRI tractography is an advanced imaging technique for quantitative mapping of the brain's structural connectivity. Whole brain tractography (WBT) data contains over hundr…
White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning
Yuqian Chen, Fan Zhang, Chaoyi Zhang +9
White matter tract microstructure has been shown to influence neuropsychological scores of cognitive performance. However, prediction of these scores from white matter tract data h…
Superficial White Matter Analysis: An Efficient Point-cloud-based Deep Learning Framework with Supervised Contrastive Learning for Consistent Tractography Parcellation across Populations and dMRI Acquisitions
Tengfei Xue, Fan Zhang, Chaoyi Zhang +7
Diffusion MRI tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections. White matter parcellation classifies tractography…
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellation
Yuqian Chen, Chaoyi Zhang, Tengfei Xue +6
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…
Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review
Fan Zhang, Alessandro Daducci, Yong He +6
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections at macro scale. Over…
FiberStars: Visual Comparison of Diffusion Tractography Data between Multiple Subjects
Loraine Franke, Daniel Karl I. Weidele, Fan Zhang +5
Tractography from high-dimensional diffusion magnetic resonance imaging (dMRI) data allows brain's structural connectivity analysis. Recent dMRI studies aim to compare connectivity…
TRAKO: Efficient Transmission of Tractography Data for Visualization
Daniel Haehn, Loraine Franke, Fan Zhang +4
Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow f…