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{
"label": "Connecting to ImageArchives",
"position": 3
}
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sidebar_position: 4
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# DCM4CHEE with Docker
1. Install Docker (https://www.docker.com/)
2. Follow the DCM4CHEE Guidelines for Running on Docker.
The easiest path is to use Docker-Compose which will start and stop multiple containers for you. There are excellent instructions provided by the DCM4CHEE team on the 'light archive' repository:
https://github.com/dcm4che/dcm4chee-arc-light/wiki/Running-on-Docker#use-docker-compose
* Create docker-compose.yml and docker-compose.env files
* Start the containers:
```` bash
docker-compose start
````
**Note:** If you are running this on Mac OSX you will probably need to change the default docker-compose.yml file slightly. Specifically, the paths that refer to /var/local/ will likely need to be changed to /opt/
3. Run the OHIF Viewer or Lesion Tracker using the dcm4cheeDIMSE.json configuration file
````bash
cd OHIFViewer
PACKAGE_DIRS="../Packages" meteor --settings ../config/dcm4cheeDIMSE.json
````
## Web Service URLs from DCM4CHEE:
Original source here: https://github.com/dcm4che/dcm4chee-arc-light/wiki/Running-on-Docker#web-service-urls
- Archive UI: <http://localhost:8080/dcm4chee-arc/ui> - if secured, login with
Username | Password | Role
--- | --- | ---
`user` | `user` | `user`
`admin` | `admin` | `user` + `admin`
- Keycloak Administration Console: <http://localhost:8080/auth>, login with Username: `admin`, Password: `admin`.
- Wildfly Administration Console: <http://localhost:9990>, login with Username: `admin`, Password: `admin`.
- Kibana UI: <http://localhost:5601>
- DICOM QIDO-RS Base URL: <http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE/rs>
- DICOM STOW-RS Base URL: <http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE/rs>
- DICOM WADO-RS Base URL: <http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE/rs>
- DICOM WADO-URI: <http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE/wado>
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# DICOM Web
[DICOMWeb](https://en.wikipedia.org/wiki/DICOMweb) refers to RESTful DICOM Services and is a recently standardized set of guidelines for exchanging medical images and imaging metadata over the internet. Not all archives fully support it yet, but it is gaining wider adoption.
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# DICOM Message Service Element
DIMSE Stands for [DICOM Message Service Element](http://dicom.nema.org/medical/dicom/current/output/chtml/part07/chapter_7.html) and is the standard method through which DICOM archives communicate. We support this messaging standard for the retrieval of study, series, and instance metadata because it is widely support. For certain PACS systems, it also (currently) provides faster query results than DICOMWeb.
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# Google Cloud Healthcare
> The [Google Cloud Healthcare API](https://cloud.google.com/healthcare/) is a powerful option for storing medical imaging data in the cloud.
An alternative to deploying your own PACS is to use a software-as-a-service provider such as Google Cloud. The Cloud Healthcare API promises to be a scalable, secure, cost effective image storage solution for those willing to store their data in the cloud. It offers an [almost-entirely complete DICOMWeb API](https://cloud.google.com/healthcare/docs/dicom) which requires tokens generated via the [OAuth 2.0 Sign In flow](https://developers.google.com/identity/sign-in/web/sign-in). Images can even be transcoded on the fly if this is desired. The Cloud Healthcare API is a very attractive option because it allows us to avoid deploying the Meteor server entirely. We can just deploy OHIF as a client-only static site application.
## Setup a Google Cloud Healthcare Project
1. Create a Google Cloud account
1. Create a project in Google Cloud
1. Enable the [Cloud Healthcare API](https://cloud.google.com/healthcare/) for your project.
1. (Optional): Create a Dataset and Data Store for storing your DICOM data
1. Enable the [Cloud Resource Manager API](https://cloud.google.com/resource-manager/) for your project.
*Note:* If you are having trouble finding the APIs, use the search box at the top of the Cloud console.
1. Go to APIs & Services > Credentials to create an OAuth Consent screen and fill in your application details.
- Under Scopes for Google APIs, click "manually paste scopes".
- Add the following scopes:
- https://www.googleapis.com/auth/cloudplatformprojects.readonly
- https://www.googleapis.com/auth/cloud-healthcare
1. Go to APIs & Services > Credentials to create a new set of credentials:
- Choose the "Web Application" type
- Set up an [OAuth 2.0 Client ID](https://support.google.com/cloud/answer/6158849?hl=en)
- Add your domain (e.g. ```http://localhost:3000```) to Authorized JavaScript origins.
- Add your domain, plus `_oauth/google` (e.g. ```http://localhost:3000/_oauth/google```) to Authorized Redirect URIs.
- Save your Client ID for later.
1. (Optional): Enable Public Datasets that are being hosted by Google: https://cloud.google.com/healthcare/docs/resources/public-datasets/
## Run the viewer with your OAuth Client ID
1. Open the `config/oidc-googleCloud.json` file and change `YOURCLIENTID` to your Client ID value.
1. Run the OHIF Viewer using the oidc-googleCloud.json configuration file
````bash
cd OHIFViewer
METEOR_PACKAGE_DIRS="../Packages" meteor npm install
METEOR_PACKAGE_DIRS="../Packages" meteor --settings ../config/oidc-googleCloud.json
````
## Running via Docker
OHIF is also providing a Docker container which can connect to Google Cloud Healthcare with a Client ID which is provided at runtime. This is a very simple method to get up and running. Internally, the container is running [Nginx](https://nginx.org/) to serve the [Standalone Viewer](../standalone-viewer/usage.md).
1. Install Docker (https://www.docker.com/)
1. Run the Docker container, providing a Client ID as an environment variable. Client IDs look like `xyz.apps.googleusercontent.com`.
````bash
docker run --env CLIENT_ID=$CLIENT_ID --publish 3000:80 ohif/viewer-google-cloud:latest
````
## Building the ohif/viewer-google-cloud Docker Image
The [ohif/viewer-google-cloud](https://cloud.docker.com/u/ohif/repository/docker/ohif/viewer-google-cloud) Docker image is built as follows. The Dockerfile and nginx.conf are in the `/dockersupport/viewer-google-cloud` folder.
1. [Install Meteor](https://www.meteor.com/install)
1. Clone the repository
```bash
git clone https://github.com/OHIF/Viewers.git
cd Viewers
```
1. Install meteor-build-client-fixed2 so you can build the Standalone Viewer
```bash
npm install -g meteor-build-client-fixed2
```
1. Build the Standalone client-only OHIF Viewer
```bash
cd OHIFViewer/
METEOR_PACKAGE_DIRS="../Packages" meteor npm install
METEOR_PACKAGE_DIRS="../Packages" meteor-build-client-fixed2 ../dockersupport/viewer-google-cloud/build -s ../config/oidc.json
```
1. Build the Docker image
```bash
cd ../dockersupport/viewer-google-cloud
docker build -t ohif/viewer-google-cloud .
```
1. Run the Docker image using an OAuth Client ID
```bash
docker run --env CLIENT_ID={$someID}.apps.googleusercontent.com --publish 3000:80 ohif/viewer-google-cloud
```
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# Connecting to Image Archives
We support DIMSE and DICOMWeb. Which one to use is up to you and depends on your PACS system. DICOMWeb requires no setup on the PACS-side whatsoever, whereas DIMSE may require you to add the 'OHIFDCM' aeTitle to the known DICOM Modalities of your Archive. This is the case for Orthanc, for example (See https://github.com/OHIF/Viewers/wiki/Orthanc-with-DIMSE).
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# Orthanc with Docker
Depending on whether or not you want uploaded studies to persist in Orthanc after Docker has been closed, there are two different methods for starting the Docker image:
## Temporary data storage
This command will start an instance of the jodogne/orthanc-plugins Docker image. *All data will be removed when the instance is stopped!*
````
docker run --rm -p 4242:4242 -p 8042:8042 jodogne/orthanc-plugins
````
## Persistent data storage
In order to allow your data to persist after the instance is stopped, you first need to create an image and attached data volume with Docker. The steps are as follows:
1. Create a persistent data volume for Orthanc to use
````
docker create --name sampledata -v /sampledata jodogne/orthanc-plugins
````
**Note: On Windows, you need to use an absolute path for the data volume, like so:**
````
docker create --name sampledata -v '//C/Users/erik/sampledata' jodogne/orthanc-plugins
````
2. Run Orthanc from Docker with the data volume attached
````
docker run --volumes-from sampledata -p 4242:4242 -p 8042:8042 jodogne/orthanc-plugins
````
3. Upload your data and it will be persisted