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COVID-Net UI: AI-Powered Clinical Decision Support Platform for COVID-19

This repo contains COVID-Net UI, an open source AI-powered clinical decision support platform for supporting different aspects in the COVID-19 clinical workflow, ranging from screening and triaging to risk stratification to treatment planning. COVID-Net UI is a containerized GUI-based platform built on top of the ChRIS platform that is designed specifically for integrating into existing clinical healthcare infrastructures, and is a core part of the COVID-Net open source initiative (http://www.covid-net.ml). The COVID-Net initiative is a global open-source initiative started by DarwinAI (http://www.darwinai.com) and the Vision and Image Processing Research Group at the University of Waterloo (http://vip.uwaterloo.ca), focussing on advancing deep learning AI in the fight against the COVID-19 pandemic.

The COVID-Net UI platform, designed specifically for clinicians and healthcare workers, lets clinicians easily leveraging the deep learning models from the main COVID-Net repo (http://www.covid-net.ml) within an easy-to-use GUI environment within the clinical workflow and features:

• A plug-in infrastructure for easy incorporation of new and updated models from the COVID-Net initiative for tackling different clinical decision support tasks in the clinical workflow for COVID-19
• PACS support for easy integration into existing clinical healthcare infrastructures
• Automatic report generation functionality for generating PDF reports of findings
• Medical image visualization functionality for easy examination of each patient case
• Patient case management functionality to easily organize patients being assessed in the COVID-19 clinical workflow
• Plug-and-play explainability (XAI) functionality to better understand decisions made by the COVID-Net AI systems

More details can be found in the paper 'COVID-Net MLSys: Designing COVID-Net for the Clinical Workflow': Click here

The COVID-Net UI platform is being developed by DarwinAI in close collaboration with the ChRIS team led by individuals in the Advanced Computing Group at Boston Children's Hospital's Fetal-Neonatal Neuroimaging and Developmental Science Center (https://fnndsc.org), with significant contributions from Red Hat, Inc. out of the Boston University/Red Hat collaboratory (https://www.bu.edu/rhcollab/projects/radiology). For more information about ChRIS, see https://chrisproject.org.

Installation

Initial Docker Swarm

docker swarm init --advertise-addr 127.0.0.1

Getting the ChRIS Backend Running

git clone https://github.com/FNNDSC/ChRIS_ultron_backEnd.git
cd ChRIS_ultron_backEnd
./make.sh -U -I -i

Getting the ChRIS Plugins

Plugins can be retrieved from Docker Hub or they can be built from source code.

Using Docker images from Docker Hub

git clone https://github.com/darwinai/covidnet_integration.git
cd <path to ChRIS_ultron_backEnd>
cp <path to covidnet_integration>/covidnet-postscript.sh . (path to covidnet_integrationis typically ../covidnet_integration)
./covidnet-postscript.sh

Uploading DICOM data to Swift

Note: PACS integration into covidnet_ui is still under development. Currently, DICOM files retrieved from the PACS server are stored within the pypx container filesystem. A method for transporting these files into the Swift filesystem to be accessible by the UI has not yet been implemented. This means that in order to test the full workflow of COVID-Net with the current implementation of PACS integration enabled, the DICOM files that were uploaded to the PACS server must also be manually uploaded to the Swift storage during setup:

When testing out COVID-Net with PACS integration, be sure to delete any PACS files currently in the Swift storage and upload the DICOM files from /covidnet_integration/images without the mock flag:

⚠️ See the covidnet_integration repository README.md for more details about how to add sample DICOMs to the COVID-Net UI.

cd <path to the covidnet_integration repo>
./make.sh
docker run --network host -v "$PWD/images/WithProtocolName/COVID-19:/images" covidnet_integration upload_swift_notify_cube.py --imageDir /images
docker run --network host -v "$PWD/images/WithProtocolName/Normal:/images" covidnet_integration upload_swift_notify_cube.py --imageDir /images
docker run --network host -v "$PWD/images/WithProtocolName/Pneumonia:/images" covidnet_integration upload_swift_notify_cube.py --imageDir /images

Deployment

docker run --rm --name covidnet_ui -p 3000:3000 -d darwinai/covidnet-ui

Once the container is up, you can access the COVID-Net UI through http://localhost:3000. Use the following username and password to log in.

• Username: chris
• Password: chris1234

Development

cd covidnet_ui
docker build -t local/covidnet-ui .
docker run --rm --name covidnet_ui -p 3000:3000 -d local/covidnet-ui

Alternatively, to run inside Docker Container:

yarn
yarn start

Tearing Down

docker stop covidnet_ui

Remove CUBE backend containers:

cd <path to ChRIS_ultron_backend>
./unmake.sh

Remove the local Docker Swarm cluster if desired:

docker swarm leave --force

Building the ChRIS Plugins From Source

NOTE:Skip this section if you have downloaded the Docker images from Docker Hub.

Building Docker Images

1. Clone the plugin repositories

https://github.com/darwinai/pl-covidnet

https://github.com/darwinai/pl-CT-covidnet

https://github.com/darwinai/pl-pdfgeneration

https://github.com/darwinai/pl-covidnet-grad-cam

2. Build the Docker Container images for these plugins by running docker build in the proper directories:

DOCKER_BUILDKIT=1 docker build -t local/pl-covidnet .
DOCKER_BUILDKIT=1 docker build -t local/pl-ct-covidnet .
DOCKER_BUILDKIT=1 docker build -t local/pl-pdfgeneration .
DOCKER_BUILDKIT=1 docker build -t local/pl-covidnet-grad-cam .

4. Type the following command to verify all images were built successfully:

docker image -ls

NOTE: If the pl-covidnet plugin fails to build with version compatibility error, open the file requirements.txt and remove the version numbers near tensorflow-estimator and tensorboard.

Uploading Plugins through the ChRIS Integration Repo

git clone https://github.com/darwinai/covidnet_integration.git
cd covidnet_integration
./uploadPlugins.sh

Note: You can install the required Python packages using this script:

 ./install_packages.sh

Install httpie using the following instructions: https://httpie.io/docs#installation

Now register the plugins on ChRIS:

1. Navigate to http://localhost:8000/chris-admin
2. login with default account with

• Username: chris
• password: chris1234

3. Navigate to plugins page: http://localhost:8000/chris-admin/plugins/plugin/
4. Click ADD PLUGIN on top right
5. choose host as compute resource
6. enter plugin name pl-covidnet
7. then save

Repeat this process for all other plugins with their respective names (pl-med2img, pl-ct-covidnet, pl-pdfgeneration).

Adding More Plug-ins and Models

If another plug-in is wished to be added to the COVID-Net UI project:

1. Follow corresponding steps of installation, creating the docker image, uploading, and registering the plug-in on ChRIS
2. Navigate to app.config.tsx, add the appropriate entry (in Xray Models, CT Models, or Plug-ins) with the plug-in's name and its alias to be used in the app

Example: Incorporating Multiple Models

The app supports the user to choose from multiple models. For testing purposes of the UI functionality, mocked models that give 2 and 4 are retrievable from the "extra" directory under src/api/models:

1. Unzip the plug-ins, and follow the above directions for adding the necessary models into pl-covidnet-2 (use the same instructions as pl-covidnet) and pl-ct-covidnet-4 (use same instructions as pl-ct-covidnet)
2. Build the docker images
3. Run upload scripts for these two plug-ins: 3a. http -a cubeadmin:cubeadmin1234 -f POST http://localhost:8010/api/v1/plugins/ dock_image=local/{NAME OF PLUG-IN}
   descriptor_file@jsonRepresentations/covidnet.json public_repo=https://github.com/FNNDSC/pl-simplefsapp name={NAME OF PLUG-IN} 3b. http -a cubeadmin:cubeadmin1234 -f POST http://localhost:8010/api/v1/plugins/ dock_image=local/{NAME OF PLUG-IN}
   descriptor_file@jsonRepresentations/ct_covidnet.json public_repo=https://github.com/FNNDSC/pl-simplefsapp name={NAME OF PLUG-IN}
4. Register the plug-ins via http://localhost:8000/chris-admin/plugins/plugin/
5. In the app.config.tsx file, add the correct entries into the Xray and CT Models section, where the key can be anything (which will be displayed to user on front-end), and the value is the plug-in name from 3a and 3b
6. Now, the front-end will present the user the added models to select from (in the drop-down menu), when creating an analysis 7a. The mocked pl-covidnet and pl-ct-covidnet models should be displayed on the drop-down and able to be selected by the user 7b. After creating the analysis, the results will be shown on the Past Predictions dashboard, where there will now be 2 or 4 classifications displayed for the scan now

### PACS Integration

The following section provides a guide for enabling COVID-Net to query and retrieve DICOM files from a local PACS server, as opposed to using mock files directly uploaded to Swift.

### Setting up an Orthanc PACS server and `pfdcm`

Instructions for setting up a local Orthanc PACS server and `pfdcm` can be found [here](https://github.com/FNNDSC/CHRIS_docs/blob/master/usecases/PACS_integration/pacs_integration.adoc). There are a few things to note when following the steps:

- Follow the steps up until the section titled **Query the PACS server**. The steps that follow are simply for querying and retrieving from PACS via the command line.
- At the step for uploading DICOM files to Orthanc, use the DICOM files from `/covidnet_integration/images` .
- Make note of the `HOST_IP` and `HOST_PORT` values used.

### Setting environment variables

In the `.env` file of the `covidnet_ui` repository, set the following environment variables to enable PACS integration, replacing `<HOST_IP>` and `<HOST_PORT>` with their respective values taken from the PACS setup instructions linked above:

```shell
REACT_APP_CHRIS_UI_DICOM_SOURCE="pacs"
REACT_APP_CHRIS_UI_PFDCM_URL="http://<HOST_IP>:<HOST_PORT>/api/v1/cmd/"

Note: for REACT_APP_CHRIS_UI_DICOM_SOURCE, using any value other than pacs will default COVID-Net to fetching files directly from Swift.