223 citations · 325 across the 16 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…
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…
Model and predict age and sex in healthy subjects using brain white matter features: A deep learning approach
Hao He, Fan Zhang, Steve Pieper +4
The human brain's white matter (WM) structure is of immense interest to the scientific community. Diffusion MRI gives a powerful tool to describe the brain WM structure noninvasive…
SupWMA: Consistent and Efficient Tractography Parcellation of Superficial White Matter with Deep Learning
Tengfei Xue, Fan Zhang, Chaoyi Zhang +6
White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts to enable quantification and visualization. Most parcellation methods…
Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
Yuqian Chen, Chaoyi Zhang, Yang Song +5
White matter fiber clustering (WMFC) enables parcellation of white matter tractography for applications such as disease classification and anatomical tract segmentation. However, t…
The White Matter Query Language: A Novel Approach for Describing Human White Matter Anatomy
Demian Wassermann, Makris Nikos, Yogesh Rathi +4
We have developed a novel method to describe human white matter anatomy using an approach that is both intuitive and simple to use, and which automatically extracts white matter tr…