58 citations · 112 across the 21 of their papers we have counts for
21 papers
DeepMultiConnectome: Deep Multi-Task Prediction of Structural Connectomes Directly from Diffusion MRI Tractography
Marcus J. Vroemen, Yuqian Chen, Yui Lo +5
Diffusion MRI (dMRI) tractography enables in vivo mapping of brain structural connections, but traditional connectome generation is time-consuming and requires gray matter parcella…
MultiCo3D: Multi-Label Voxel Contrast for One-Shot Incremental Segmentation of 3D Neuroimages
Hao Xu, Tengfei Xue, Dongnan Liu +6
3D neuroimages provide a comprehensive view of brain structure and function, aiding in precise localization and functional connectivity analysis. Segmentation of white matter (WM)…
TractCloud-FOV: Deep Learning-based Robust Tractography Parcellation in Diffusion MRI with Incomplete Field of View
Yuqian Chen, Leo Zekelman, Yui Lo +7
Tractography parcellation classifies streamlines reconstructed from diffusion MRI into anatomically defined fiber tracts for clinical and research applications. However, clinical s…
Medical Image Registration Meets Vision Foundation Model: Prototype Learning and Contour Awareness
Hao Xu, Tengfei Xue, Jianan Fan +7
Medical image registration is a fundamental task in medical image analysis, aiming to establish spatial correspondences between paired images. However, existing unsupervised deform…
Enhancing Advanced Visual Reasoning Ability of Large Language Models
Zhiyuan Li, Dongnan Liu, Chaoyi Zhang +3
Recent advancements in Vision-Language (VL) research have sparked new benchmarks for complex visual reasoning, challenging models' advanced reasoning ability. Traditional Vision-La…
Enhancing Robustness to Noise Corruption for Point Cloud Recognition via Spatial Sorting and Set-Mixing Aggregation Module
Dingxin Zhang, Jianhui Yu, Tengfei Xue +3
Current models for point cloud recognition demonstrate promising performance on synthetic datasets. However, real-world point cloud data inevitably contains noise, impacting model…
TractGraphFormer: Anatomically Informed Hybrid Graph CNN-Transformer Network for Interpretable Sex and Age Prediction from Diffusion MRI Tractography
Yuqian Chen, Fan Zhang, Meng Wang +10
The relationship between brain connections and non-imaging phenotypes is increasingly studied using deep neural networks. However, the local and global properties of brain white ma…
A Deep Network for Explainable Prediction of Non-Imaging Phenotypes using Anatomical Multi-View Data
Yuxiang Wei, Yuqian Chen, Tengfei Xue +6
Large datasets often contain multiple distinct feature sets, or views, that offer complementary information that can be exploited by multi-view learning methods to improve results.…
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…
A Registration- and Uncertainty-based Framework for White Matter Tract Segmentation With Only One Annotated Subject
Hao Xu, Tengfei Xue, Dongnan Liu +5
White matter (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI) plays an important role in the analysis of human health and brain diseases. However, the a…
GeoLab: Geometry-based Tractography Parcellation of Superficial White Matter
Nabil Vindas, Nicole Labra Avila, Fan Zhang +3
Superficial white matter (SWM) has been less studied than long-range connections despite being of interest to clinical research, andfew tractography parcellation methods have been…
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…
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…
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…