223 citations · 325 across the 16 of their papers we have counts for
9 papers · 1 filter
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…