7 papers
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…
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…
Cross-domain Fiber Cluster Shape Analysis for Language Performance Cognitive Score Prediction
Yui Lo, Yuqian Chen, Dongnan Liu +8
Shape plays an important role in computer graphics, offering informative features to convey an object's morphology and functionality. Shape analysis in brain imaging can help inter…
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…
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…
TractShapeNet: Efficient Multi-Shape Learning with 3D Tractography Point Clouds
Yui Lo, Yuqian Chen, Dongnan Liu +9
Brain imaging studies have demonstrated that diffusion MRI tractography geometric shape descriptors can inform the study of the brain's white matter pathways and their relationship…