Gliomarad

Code for radiogenomic inference using radiomics and deep convolutional features

Installation

The following command will clone a copy of Gadnet to your computer using git:

git clone https://github.com/ecalabr/gliomarad.git

Data directory tree setup

Gliomarad expects your image data to be in Nifti format with a specific directory tree. The following example starts with any directory (referred to as data_dir).

data_dir/

This is an example of the base directory for all of the image data that you want to use. All subdirectories in this folder should contain individual patient image data.

data_dir/123456/

This is an example of an individual patient study directory. The directory name is typically a patient ID, but can be any folder name that does not contain the "_" character

data_dir/123456/123456_T1gad.nii.gz

This is an example of a single patient image. The image file name must start with the patient ID (i.e. the same as the patient directory name) followed by a "_" character. All Nifti files are expected to be g-zipped.

Usage

Train

The following command will train the network using the parameters specified in the param file (-p):

python train.py -p params/params.json

For help with parameter files, please refer to a separate markdown file in the "params" subdirectory of this project.

Training outputs will be located in the model directory as specified in the param file.

Citation

Manuscript currently under review. Please check back later.