Beyond FA mean of AD, MD, FA, RDAdd commentMore actions

To build this Docker container, clone the repository and run the following command in the root directory:

DOCKER_BUILDKIT=1 sudo docker build -t beyondfa_mix .

The Docker runs the code from scripts/entrypoint.sh.

Running the Docker

Your Docker container should be able to read input data from /input and write output data to /output. Intermediate data should be written to /tmp. The input data will be a .mha file containing the diffusion MRI data with gradient table information contained in a .json file. The input file will be in /input/images/dwi-4d-brain-mri/, with gradient table information at /input/dwi-4d-acquisition-metadata.json. Your Docker should write a JSON list to the output directory with the name /output/features-128.json. Your JSON list must contain 128 values. You may zero-pad the list if you wish to provide fewer than 128 values.

See scripts/convert_mha_to_nifti.py and scripts/convert_json_to_bvalbvec.py for scripts to convert the .mha to .nii.gz and the .json to .bval and .bvec files.

To run this Docker:

input_dir="/"            
output_dir="/"                                                                                        
DOCKER_NOOP_VOLUME="beyondfa_mix3-volume"

mkdir -p "$output_dir"

sudo docker volume rm "$DOCKER_NOOP_VOLUME" > /dev/null 2>&1
sudo docker volume create "$DOCKER_NOOP_VOLUME" > /dev/null
sudo docker run \
    -it \
    --platform linux/amd64 \
    --network none \
    --gpus all \
    --rm \
    --volume "$input_dir":/input:ro \
    --volume "$output_dir":/output \
    --volume "$DOCKER_NOOP_VOLUME":/tmp \
    beyondfa_mix3
sudo chmod -R 777 "$output_dir"

beyond_fa_microstruct_mix

beyond_fa_microstruct_mix

beyondfa_microstruct_mix

Beyond FA mean of AD, MD, FA, RD

Diffusion Tensor Imaging Metrics

FA (Fractional Anisotropy) is a scalar value between 0 and 1 that quantifies how directional water diffusion is within a voxel in diffusion MRI, especially in white matter.

$$FA = \sqrt{\frac{3}{2}} \cdot \frac{\sqrt{(\lambda_1 - MD)^2 + (\lambda_2 - MD)^2 + (\lambda_3 - MD)^2}}{\sqrt{\lambda_1^2 + \lambda_2^2 + \lambda_3^2}}$$

MD (Mean Diffusivity) is the arithmetic mean of the three eigenvalues of the diffusion tensor.

$$MD = \frac{\lambda_1 + \lambda_2 + \lambda_3}{3}$$

AD (Axial Diffusivity) captures diffusion along the primary fiber direction (largest eigenvalue), used as a marker of axonal integrity.

$$AD = \lambda_1$$

RD (Radial Diffusivity) is the average of the two minor eigenvalues, associated with myelin integrity.

$$RD = \frac{\lambda_2 + \lambda_3}{2}$$

Building the Docker

To build this Docker container, clone the repository and run the following command in the root directory:

DOCKER_BUILDKIT=1 sudo docker build -t beyondfa_mix .

The Docker runs the code from scripts/entrypoint.sh.

Running the Docker

Your Docker container should be able to read input data from /input and write output data to /output. Intermediate data should be written to /tmp. The input data will be a .mha file containing the diffusion MRI data with gradient table information contained in a .json file. The input file will be in /input/images/dwi-4d-brain-mri/, with gradient table information at /input/dwi-4d-acquisition-metadata.json. Your Docker should write a JSON list to the output directory with the name /output/features-128.json. Your JSON list must contain 128 values. You may zero-pad the list if you wish to provide fewer than 128 values.

See scripts/convert_mha_to_nifti.py and scripts/convert_json_to_bvalbvec.py for scripts to convert the .mha to .nii.gz and the .json to .bval and .bvec files.

To run this Docker:

input_dir=".../input_data"
output_dir=".../output_data"                                                                                      
DOCKER_NOOP_VOLUME="beyondfa_mix3-volume"

mkdir -p "$output_dir"

sudo docker volume rm "$DOCKER_NOOP_VOLUME" > /dev/null 2>&1
sudo docker volume create "$DOCKER_NOOP_VOLUME" > /dev/null
sudo docker run \
    -it \
    --platform linux/amd64 \
    --network none \
    --gpus all \
    --rm \
    --volume "$input_dir":/input:ro \
    --volume "$output_dir":/output \
    --volume "$DOCKER_NOOP_VOLUME":/tmp \
    beyondfa_mix3
sudo chmod -R 777 "$output_dir"