1 citations · 1 across the 7 of their papers we have counts for
7 papers
A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter
Yifei Sun, James M. Shine, Robert D. Sanders +4
The white matter of the brain is organised into axonal bundles that support long-range neural communication. Although diffusion MRI (dMRI) enables detailed mapping of these pathway…
From Promise to Practical Reality: Transforming Diffusion MRI Analysis with Fast Deep Learning Enhancement
Xinyi Wang, Michael Barnett, Frederique Boonstra +15
Fiber orientation distribution (FOD) is an advanced diffusion MRI modeling technique that represents complex white matter fiber configurations, and a key step for subsequent brain…
Age Sensitive Hippocampal Functional Connectivity: New Insights from 3D CNNs and Saliency Mapping
Yifei Sun, Marshall A. Dalton, Robert D. Sanders +5
Grey matter loss in the hippocampus is a hallmark of neurobiological aging, yet understanding the corresponding changes in its functional connectivity remains limited. Seed-based f…
Voxel-Level Brain States Prediction Using Swin Transformer
Yifei Sun, Daniel Chahine, Qinghao Wen +5
Understanding brain dynamics is important for neuroscience and mental health. Functional magnetic resonance imaging (fMRI) enables the measurement of neural activities through bloo…
Predicting Human Brain States with Transformer
Yifei Sun, Mariano Cabezas, Jiah Lee +4
The human brain is a complex and highly dynamic system, and our current knowledge of its functional mechanism is still very limited. Fortunately, with functional magnetic resonance…
Enhancing Angular Resolution via Directionality Encoding and Geometric Constraints in Brain Diffusion Tensor Imaging
Sheng Chen, Zihao Tang, Mariano Cabezas +6
Diffusion-weighted imaging (DWI) is a type of Magnetic Resonance Imaging (MRI) technique sensitised to the diffusivity of water molecules, offering the capability to inspect tissue…
How Much Data are Enough? Investigating Dataset Requirements for Patch-Based Brain MRI Segmentation Tasks
Dongang Wang, Peilin Liu, Hengrui Wang +11
Training deep neural networks reliably requires access to large-scale datasets. However, obtaining such datasets can be challenging, especially in the context of neuroimaging analy…