mturja-vf-ic-bd Goto Github PK

2019_cni_trainingrelease

Training data release for Connectomics in NeuroImaging - Transfer Learning Challenge (CNI-TLC). For more details, see http://miccai.brainconnectivity.net

active-shape-model

ad-longitudinal-smoothing

This is a project to make the longitudinal brain networks of a patient consistent in some sense. The longitudinal brain networks are generated from MRI scans. This scans contain noise. To analysis the change of brain network over time it is important to increase signal to noise ratio. We use some constraints on the generated brain network to accomplish this task.

adni_processing

This tool generates brain connectivity matrix for ADNI data.

andi_graph_analysis

annot2json

autoencoderpractice

A practice session to learn autoencoder and variational autoencoder

bios772_final_project

checkforutilizationindevice

cnslab_fmri

CNS (Computational Neuroscience) Lab project for age/sex classification of fMRI scans

comp562_ml_project

This is the final project for the Machine Learning course COMP562.001.SP19. The project is on graph classification using Graph Convolutional Network.

comp775-assignment1

comp775-assignment3-registration

cplot

Circle Plot for Brain Network

deepgraphdmd

Deep learning based Koopman operator for graph dynamical systems.

deepgraphkoopmanoperator

deviceupdated

diffusion_u_net

editlabel

extensionsindex

Slicer extensions index

fmri_predict

predicting fmri activaties from connectome

gae_in_pytorch

Graph Auto-Encoder in PyTorch

gcnrnn

geomcnn

google-research-knf

Google Research KNF

graph-generation

GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

graphdmd

Dynamic mode decomposition with dependent structure among observables (Graph DMD)

groupwisegraphlearning

image-blender

image-sticher