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Found 10 papers, 5 papers with code
Supervised Tractogram Filtering using Geometric Deep Learning
A tractogram is a virtual representation of the brain white matter.
Tractogram filtering of anatomically non-plausible fibers with geometric deep learning
The intuitive idea is to model a fiber as a point cloud and the goal is to investigate whether and how a geometric deep learning model might capture its anatomical properties.
Automatic Tissue Segmentation with Deep Learning in Patients with Congenital or Acquired Distortion of Brain Anatomy
Brains with complex distortion of cerebral anatomy present several challenges to automatic tissue segmentation methods of T1-weighted MR images.
A Test for Shared Patterns in Cross-modal Brain Activation Analysis
In the last decade, the identification of shared activity patterns has been mostly framed as a supervised learning problem.
Comparison of Distances for Supervised Segmentation of White Matter Tractography
For these reasons, in this work we compare many streamline distance functions available in the literature.
Mapping Tractography Across Subjects
Diffusion magnetic resonance imaging (dMRI) and tractography provide means to study the anatomical structures within the white matter of the brain.
The Kernel Two-Sample Test for Brain Networks
In clinical and neuroscientific studies, systematic differences between two populations of brain networks are investigated in order to characterize mental diseases or processes.
The Approximation of the Dissimilarity Projection
We investigate the degree of approximation of this projection under different prototype selection policies and prototype set sizes in order to characterise its use on tractography data.
MEG Decoding Across Subjects
On a face vs. scramble task MEG dataset of 16 subjects, we compare the standard approach of not modelling the differences across subjects, to the proposed one of combining TTL and ensemble learning.
