most citedTractoFormer: A Novel Fiber-level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2022

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…

q-bio.NC2022

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…

cs.CV2022

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…

eess.IV2022★ 2 cited

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…

cs.CV2022

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…