Results and code for MICCAI 2017 paper "Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification"
data (coming) -- sample data for running scripts. Full data will be available at IGC website.
results -- folder with full original results and outputs of scripts. raw_results -- data computed in preparation of the paper, script_results -- outputs of sample scripts
*scripts (coming) * -- scripts we used to calculate pairwise and gender classification and ICC.
pics -- some of the graphs.
pdf -- paper pdf.
Scripts currently requires Python 3.4 or later to run. Please install
pip via the package manager of your operating system if it is not included
already. Also you need R language:
$ apt-get install r-base
And you need
psych package. To install it run following in R shell:
> install.packages('psych', dependencies=TRUE, repos='http://cran.us.r-project.org')
To install needed Python dependencies run next in terminal:
$ pip3 install -r https://github.com/USC-IGC/connectome-evaluation-miccai2017/blob/master/requirements.txt
There are three main scripts in
An argument for these scripts is a string of format:
$ ./classificate_pairwise.py dataset-normalization-tractography-reconstruction_model-atlas_type
$ ./classificate_pairwise.py BNU_1-max-deter-csd-con_aparc68+subcort
All calculated combinations you can find in
`combinations_for_pairwise_classification.txt'. More information about
parameters you can find in the article.
To test calculated results you can use
test_results.py script. Just run it
and choose directory you want to check:
$ ./test_results.py 0 /gender_results/ 1 /icc_results/BNU_1/ 2 /icc_results/HNU_1/ 3 /icc_results/IPCAS_1/ 4 /pairwise_results/ Please choose what directories to check: $ 0 /gender_results/ 1/327 are similar 0 ain't similar
Here we calculated results for one combination and script said us the result the same as we used for the article.