Segmentation tool for the delineation and volumetric quantification of the choroid plexus
If you have already installed Docker, you can get the kilianhett/chp_seg:1.0.0 image from Docker Hub repository:
sudo docker pull kilianhett/chp_seg:1.0.0
Choroid plexus segmentation software currently only supports CPU
sudo docker run -v /absolute_path_to_folder/:/data/in -v /absolute_path_to_folder/:/data/out kilianhett/chp_seg:1.0.0 --sequence_type T1 --name_pattern <name_of_image>
See Installation instructions for detailed instructions on how to install all the dependencies. See How to use Chp_Seg for detailed instructions on how to use Chp_Seg.
If you use this software please cite the [associated publication]
Eisma, Jarrod J., et al. "Deep learning segmentation of the choroid plexus from structural magnetic resonance imaging (MRI): validation and normative ranges across the adult lifespan." Fluids and Barriers of the CNS 21.1 (2024): 1-13.
To run this Docker image on a CPU, you will need:
- a x86_64 CPU
- At least 6GB of RAM
- GNU/Linux [supported distributions], MacOS, or Windows 10/11 with WSL [supported versions]
- Docker >= 19.03
- Chp_seg Docker image
- MRI files in nifti format
Docker may be installed on supported versions of [GNU/Linux] or [Windows 10/11 with WSL]. The docker image can also be transformed in a [Singularity image]
Here are the detailed installation instructions on MacOS [instructions]
Here are the detailed installation instructions on Ubuntu (18.04 or above).
Install Docker from the official repository [instructions].
(Docker no longer releases updated packages for Ubuntu 16.04)
#Uninstall old versions of docker
sudo apt-get remove docker docker-engine docker.io containerd runc
#Install using the official repository
sudo apt-get update
sudo apt-get install apt-transport-https ca-certificates curl gnupg-agent software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo apt-key fingerprint 0EBFCD88
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo apt-get update
sudo apt-get install docker-ce docker-ce-cli containerd.io
#Verify that Docker Engine is installed correctly
sudo docker run hello-world
# it may download the hello-world docker image and then print "Hello from Docker!" and other information.
Here are the detailed installation instructions on Windows 10 or 11.
You need:
- Windows 10 64-bit: Home or Pro 2004 (build 19041) or higher, or Enterprise or Education 1909 (build 18363) or higher.
- Windows 11 64-bit: Home or Pro version 21H2 or higher, or Enterprise or Education version 21H2 or higher.
To check your Windows version and build number, select Windows logo key + R, type winver, select OK. You can update to the latest Windows version by selecting Start > Settings > Windows Update > Check for updates.
BIOS-level hardware virtualization support must be enabled.
You can check the Performance tab on the Task Manager to see if virtualization is enabled, see virtualization support.
Install Windows Subsystem for Linux (WSL) 2 [instructions]
Open PowerShell as Administrator (Start menu > PowerShell > right-click > Run as Administrator) and enter this command:
wsl --install
It should install the last Ubuntu LTS. You may need to reboot your machine.
You can check that WSL version 2 was installed: Open PowerShell as Administrator (Start menu > PowerShell > right-click > Run as Administrator) and enter this command:
wsl -l -v
Launch Ubuntu (Start menu > ubuntu). It should ask to create a default user. You may upgrade the system:
sudo apt-get update
sudo apt-get upgrade
This Docker image requires T1-weighted, T2-weighted, or FLAIR images in nifti format (.nii or .nii.gz) as inputs.
To convert your DICOM files into nifti format, you can use dcm2niix, a multiplatform and open-source software.
For each processed image, the following files will be produced and stored separately in a folder named filename (where filename is replaced by the original filename):
- filename.nii.gz: Native image corrected for N4 inhomogeneity
- filename_chp_mask.nii.gz: Segmentation maps of the choroid plexus structures
The Docker image has the following arguments:
[--sequence_type `T1/T2/FLAIR`] [--name_pattern `<filename/pattern>`] [--overwrite True/False (default=False]
T1/T2/FLAIR: Type of sequence defined as input T1, T2, or FLAIR.<filename/pattern>: Filter the filenames with a specific pattern in the input directory.<overwrite>: Allow to replace already existing processing output.