DLICV - Deep Learning Intra Cranial Volume

Overview

DLICV uses a trained nnUNet model to compute the intracranial volume from structural MRI scans in the nifti image format, oriented in LPS orientation.

Installation

As a python package

pip install dlicv

Directly from this repository

git clone https://github.com/georgeaidinis/DLICV
cd DLICV
conda create -n DLICV -y python=3.8 && conda activate DLICV
pip install .

Usage

A pre-trained nnUNet model can be found in the DLICV-0.0.0 release as an artifact. Feel free to use it under the package's license.

Import as a python package

from dlicv.compute_icv import compute_volume

# Assuming your nifti file is named 'input.nii.gz'
volume_image = compute_volume("input.nii.gz", "output.nii.gz", "path/to/model/")

From the terminal

DLICV --input input.nii.gz --output output.nii.gz --model path/to/model

Replace the input.nii.gz with the path to your input nifti file, as well as the model path.

Example:

Assuming a file structure like so:

.
├── in
│   ├── input1.nii.gz
│   ├── input2.nii.gz
│   └── input3.nii.gz
├── model
│   ├── fold_0
│   ├── fold_1
│   │   ├── debug.json
│   │   ├── model_final_checkpoint.model
│   │   ├── model_final_checkpoint.model.pkl
│   │   ├── model_latest.model
│   │   ├── model_latest.model.pkl
│   └── plans.pkl
└── out

An example command might be:

DLICV --input path/to/input/ --output path/to/output/ --model path/to/model/

Using the docker container

In the docker container, the.

Contact

For more information, please contact CBICA Software.