Installation#
Docker image#
We recommend to use our docker image to run nesvor.
Install docker and NVIDIA container toolkit#
You may follow this guide to install docker and NVIDIA container toolkit.
Download NeSVoR image#
Pull the latest NeSVoR image from docker hub.
docker pull junshenxu/nesvor
Note: our latest image was built with CUDA 11.7.
Run NeSVoR with docker#
You may run a container in an iterative way.
docker run -it --gpus all junshenxu/nesvor:v0.5.0
nesvor -h
You may also run the nesvor command directly as follows.
docker run --rm --gpus all \
-v <path-to-inputs>:/incoming:ro -v <path-to-outputs>:/outgoing:rw \
junshenxu/nesvor:v0.5.0 \
nesvor reconstruct \
--input-stacks /incoming/stack-1.nii.gz ... /incoming/stack-N.nii.gz \
--thicknesses <thick-1> ... <thick-N> \
--output-volume /outgoing/volume.nii.gz
From source#
Prerequisites#
If you are installing from source, you will need:
An NVIDIA GPU;
Python 3.8 or later;
GCC/G++ 7.5 or higher;
CUDA v10.2 or higher;
CMake v3.21 or higher.
See tiny-cuda-nn for more about prerequisites.
Get the NeSVoR source#
Since the master branch might be messy sometimes, it is recommanded to clone a specific release.
git clone https://github.com/daviddmc/NeSVoR --branch v0.5.0
cd NeSVoR
Install dependencies#
pip install -r requirements.txt
Install PyTorch extension of tiny-cuda-nn. Make sure the installed CUDA version mismatches the version that was used to compile PyTorch. Then, run the following command (see this for more details)
pip install git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch
Other dependencies#
Some functionalities of NeSVoR require extra dependencies.
Fetal brain masking (MONAIfbs)#
To use the MONAIfbs model for fetal brain ROI masking, MONAI need to be installed. Check out the orginal repo for more details.
pip install monai>=0.3.0
N4 bias field correction#
To use the N4 algorithm for bias field correction, SimpleITK need to be installed.
pip install SimpleITK
3D IQA#
The 3D MR quality assessment tool uses a pretrained Tensorflow model. Tensorflow needs to be installed to enable this tool. Check out the orginal repo for more details.
Install NeSVoR#
The last step is to install NeSVoR itself.
pip install -e .