TotalSegmentator-AIDE

TotalSegmentator packaged as an AIDE Application, based on the open-source MONAI Application Package (MAP) standard.

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TotalSegmentator MAP workflow

The input to the TotalSegmentator MAP is a folder containing CT DICOM .dcm files. The output is an RT Struct DICOM .dcm file containing the contours of all the segmented regions.

The TotalSegmentator MAP consists of three operators:

dcm2nii_operator.py – converts the input CT DICOM files to NIfTI format required by TotalSegmentator, using dcm2niix
totalsegmentator_operator.py – runs TotalSegmentator
rtstructwriter_operator.py – converts the output segmentations from NIfTI to DICOM RT Struct format, using rt-utils
clinrev_pdf_operator.py – creates a DICOM encapsulated PDF showing three views of the input CT dataset overlaid with the segmentations generated by TotalSegmentator

Developer Guidelines

Prerequisites

GPU-enabled machine
Docker
- Required for running the MAP. Not required for running source code

Setup

Download

git clone https://github.com/GSTT-CSC/TotalSegmentator-AIDE.git

Setup virtual env

cd TotalSegmentator-AIDE

python -m venv venv
source venv/bin/activate

pip install --upgrade pip setuptools wheel
pip install -r requirements.txt

Create input and output directories

mkdir input output

Run source code with MONAI Deploy

Ensure Python venv running
Copy DICOM .dcm files to input/ directory

monai-deploy exec app -i input/ -o -output/

# alternatively:
python app -i input/ -o output/

Build and run as MONAI Application Package (MAP)

Ensure Python venv running
Ensure Docker running
Copy DICOM .dcm files to input/ directory

Important: we create an initial MAP map-init upon which we build any 3rd-party non-Python software (e.g. dcm2niix). The final MAP is called map

# Initial packaging of MAP
monai-deploy package app --tag ghcr.io/gstt-csc/totalsegmentator-aide/map-init:0.2.0 -l DEBUG

# Build 3rd-party software on top of MAP
docker build -t ghcr.io/gstt-csc/totalsegmentator-aide/map:0.2.0 app/

# Test MAP with MONAI Deploy
monai-deploy run ghcr.io/gstt-csc/totalsegmentator-aide/map:0.2.0 input/ output/

# Push initial MAP and final MAP to GHCR
docker push ghcr.io/gstt-csc/totalsegmentator-aide/map-init:0.2.0
docker push ghcr.io/gstt-csc/totalsegmentator-aide/map:0.2.0

Optional

Enter Docker container for testing

docker run --gpus all -it --rm -v /TotalSegmentator-AIDE/input:/var/monai/input/ --entrypoint /bin/bash ghcr.io/gstt-csc/totalsegmentator-aide/map:0.2.0

Run on specified GPU if machine has >1 available

CUDA_VISIBLE_DEVICES=2 monai-deploy run ghcr.io/gstt-csc/totalsegmentator-aide/map:0.2.0 input/ output/

Reminder: if GHCR requires Personal Access Token

echo $CR_PAT | docker login ghcr.io -u <github-username> --password-stdin
docker push ghcr.io/gstt-csc/totalsegmentator-aide/map-init:0.2.0

GitHub Packages

Note: two containers are present under GitHub Packages:

The map version is for general usage and deployment. The map-init version is for developers who wish to build the MAP from scratch as part of the two-step build process described above.

DICOM Encapsulated PDF

AIDE Clinical Review is a user interface within AIDE for assessing the quality of AI results. It can display DICOM Encapsulated PDFs. The screenshot below is an example PDF generated by clinrev_pdf_operator.py:

Running on AIDE

To run TotalSegmentator on AIDE, two files from the app/workflows directory are required, namely:

totalsegmentator.json – AIDE Clinical Workflow file.
- Effectively a sequence of tasks run on AIDE
totalsegmentator-argo-template.yaml – Argo Workflow Template file.
- Called by the AIDE Clinical Workflow file. Executes the Totalsegmentator-AIDE MAP using Argo. This is the central task within the AIDE Clinical Workflow file.

The app/workflows directory also contains four illustrative Argo Workflow Templates depending on system performance. low, medium, high and dgx examples are provided with different CPU and RAM settings.

jordimassaguerpla/TotalSegmentator-AIDE