ALARM: automatic liver attenuation estimation

[project page] [Medical Physcis paper]

The liver attenuation estimations can be achieved from a single CT abdomen scan

It has been implemented as a single Docker.

+ The code and docker are free for noncommercial purposes.
+ The licence.md shows the terms for commercial and for-profit purposes.
- Please cite the following MICCAI/NeuroImage paper, if you used the ALARM liver attenuation estimation.

The papers can be found [Medical Physcis paper], whole full citation are

Yuankai Huo, James G. Terry, Jiachen Wang, Sangeeta Nair, Thomas A. Lasko, Barry I. Freedman, Jeffery J. Carr, and Bennett A. Landman. "Fully Automatic Liver Attenuation Estimation combing CNN Segmentation and Morphological Operations." Medical physics (2019).

Quick Start

Get our docker image

sudo docker pull masidocker/public:liver_attenuation_v3_0_4

Run ALARM liver attenuation segmentation

You can run the following command or change the "input_dir", then you will have the final segmentation results in output_dir

# you need to specify the input directory
export input_dir=/home/input_dir   
# make that directory
sudo mkdir $input_dir
# put dicom images to the $input_dir directly without subfolders
# set output directory
export output_dir=$input_dir/output
#run the docker if your input_dir contains dicom files
sudo nvidia-docker run -it --rm -v $input_dir:/INPUTS/ -v $output_dir:/OUTPUTS masidocker/public:liver_attenuation_v3_0_3 /extra/run_deep_wholebody_dicom.sh

#run the docker if your input_dir contains nifti
sudo nvidia-docker run -it --rm -v $input_dir:/INPUTS/ -v $output_dir:/OUTPUTS masidocker/public:liver_attenuation_v3_0_3 /extra/run_deep_wholebody_nifti.sh

Here is a testing scan

https://vanderbilt.box.com/shared/static/zqbsc1fzi5csgo00urstv8666ligkqhk.gz

Detailed envrioment setting

Testing platform

• Ubuntu 16.04
• cuda 8.0/9.0
• Docker version 1.13.1-cs9
• Nvidia-docker version 1.0.1 to 2.0.3

install Docker

sudo apt-get install apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu bionic stable"
sudo apt-get update
sudo apt-get install docker-ce

install Nvidia-Docker

curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update
sudo apt-get install -y nvidia-docker2

[Version Updates] 2022-04-13: update the v3.0.4 from v3.0.3. Address the problem with JP-LS compressed dicom images. Update dcm2niix version to v1.0.20211006 (JP2:OpenJPEG) (JP-LS:CharLS) 2020-02-08: update the v3.0.3 from v3.0.2. Add a pdf generation function to generate a pdf report 2019-08-03: update the v3.0.2 from v3.0.0. To address the error in resampling. The skimage.resize is included.