activity
20222026
most citedSuperficial White Matter Analysis: An Efficient Point-cloud-based Deep Learning Framework with Supervised Contrastive Learning for Consistent Tractography Parcellation across Populations and dMRI Acquisitions

58 citations · 146 across the 36 of their papers we have counts for

collaborators
Showing eess.IVShow all

14 papers · 1 filter

eess.IV2025

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…

eess.IV2025★ 2 cited

A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography

Yui Lo, Yuqian Chen, Dongnan Liu +8

Shape measures have emerged as promising descriptors of white matter tractography, offering complementary insights into anatomical variability and associations with cognitive and c…

eess.IV2025

DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI Tractography

Haolin He, Ce Zhu, Le Zhang +9

Brain nuclei are clusters of anatomically distinct neurons that serve as important hubs for processing and relaying information in various neural circuits. Fine-scale parcellation…

eess.IV2024

A Novel Deep Learning Tractography Fiber Clustering Framework for Functionally Consistent White Matter Parcellation Using Multimodal Diffusion MRI and Functional MRI

Jin Wang, Bocheng Guo, Yijie Li +7

Tractography fiber clustering using diffusion MRI (dMRI) is a crucial strategy for white matter (WM) parcellation. Current methods primarily use the geometric information of fibers…

eess.IV2024

DINeuro: Distilling Knowledge from 2D Natural Images via Deformable Tubular Transferring Strategy for 3D Neuron Reconstruction

Yik San Cheng, Runkai Zhao, Heng Wang +5

Reconstructing neuron morphology from 3D light microscope imaging data is critical to aid neuroscientists in analyzing brain networks and neuroanatomy. With the boost from deep lea…

eess.IV2024

DDEvENet: Evidence-based Ensemble Learning for Uncertainty-aware Brain Parcellation Using Diffusion MRI

Chenjun Li, Dian Yang, Shun Yao +14

In this study, we developed an Evidence-based Ensemble Neural Network, namely EVENet, for anatomical brain parcellation using diffusion MRI. The key innovation of EVENet is the des…