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{
"label": "Data Sources",
"position": 2
}

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---
sidebar_position: 6
sidebar_label: Configuration UI
---
# Configuration UI
OHIF provides for a generic mechanism for configuring a data source. This is
most useful for those organizations with several data sources
that share common (path) hierarchies. For example, an organization may have several DICOM stores
in the Google Cloud Healthcare realm where each is organized into various projects,
location, data sets and DICOM stores.
By implementing the `BaseDataSourceConfigurationAPI` and
`BaseDataSourceConfigurationAPIItem` in an [OHIF extension](../../platform/extensions/index.md), a data source can
be made configurable via the generic UI as is depicted below for a
Google Cloud Healthcare data source.
![Data source configuration UI](../../assets/img/data-source-configuration-ui.png)
:::tip
A datasource root URI can be [fully or partially specified](../../deployment/google-cloud-healthcare.md#configuring-google-cloud-healthcare-as-a-datasource-in-ohif)
in the OHIF configuration file.
:::
## `BaseDataSourceConfigurationAPIItem` interface
Each (path) item of a data source is represented by an instance of this interface.
At the very least each of these items must expose two properties:
|Property |Description|
|---------|-----------|
|id|a string that uniquely identifies the item|
|name|a human readable name for the item|
Note that information such as where in the path hierarchy the item exists
has been omitted, but can be added in any concrete class that might implement this
interface. For example, the the Google Cloud Healthcare implementation of this
interface (`GoogleCloudDataSourceConfigurationAPIItem`) adds an `itemType`
(i.e. projects, locations, datasets, or dicomStores) and `url`.
## `BaseDataSourceConfigurationAPI` interface
The implementation of this interface is at the heart of the configuration process.
It possesses several methods for building up a data source path based on various
`BaseDataSourceConfigurationAPIItem` objects that are set via calls to the `setCurrentItem`
method.
The constructor for the concrete class implementation should accept whatever
parameters are necessary for configuring the data source. One argument
to the constructor must be the string identifying the name of the data source
to be configured. Furthermore, considering that the `ExtensionManager` possesses
API to configure and update data sources, it too will likely be an argument to
the constructor. See [Creation via Customization Module](#creation-via-customization-module)
for more information on how the constructor is invoked via a factory method.
For an example implementation of this interface see `GoogleCloudDataSourceConfigurationAPI`.
### Interface Methods
Each of the following subsections lists a method of the interface with a description
detailing what the method should do.
#### `getItemLabels`
Gets the i18n labels (i.e. the i18n lookup keys) for each of the configurable items
of the data source configuration API. For example, for the Google Cloud Healthcare
API, this would be `['Project', 'Location', 'Data set', 'DICOM store']`.
Besides the configurable item labels themselves, several other string look ups
are used base on EACH of the labels returned by this method.
For instance, for the label `{itemLabel}`, the following strings are fetched for
translation...
1. `No {itemLabel} available`
- used to indicate no such items are available
- for example, for Google, `No Project available` would be 'No projects available'
2. `Select {itemLabel}`
- used to direct selection of the item
- for example, for Google, `Select Project` would be 'Select a project'
3. `Error fetching {itemLabel} list`
- used to indicate an error occurred fetching the list of items
- usually accompanied by the error itself
- for example, for Google, `Error fetching Project list` would be 'Error fetching projects'
4. `Search {itemLabel} list`
- used as the placeholder text for filtering a list of items
- for example, for Google, `Search Project list` would be 'Search projects'
#### `initialize`
Initializes the cloud server API and returns the top-level sub-items
that can be chosen to begin the process of configuring a data source.
For example, for the Google Cloud Healthcare API, this would perform the initial request
to fetch the top level projects for the logged in user account.
#### `setCurrentItem`
Sets the current path item that is passed as an argument to the method and
returns the sub-items of that item
that can be further chosen to configure a data source.
When setting the last configurable item of the data source (path), this method
returns an empty list AND configures the active data source with the selected
items path.
For example, for the Google Cloud Healthcare API, this would take the current item
(say a data set) and queries and returns its sub-items (i.e. all of the DICOM stores
contained in that data set). Furthermore, whenever the item to set is a DICOM store,
the Google Cloud Healthcare API implementation would update the OHIF data source
associated with this instance to point to that DICOM store.
#### `getConfiguredItems`
Gets the list of items currently configured for the data source associated with
this API instance. The resultant array must be the same length as the result of
`getItemLabels`. Furthermore the items returned should correspond (index-wise)
with the labels returned from `getItemLabels`.
## Creation via Customization Module
The generic UI (i.e. `DataSourceConfigurationComponent`) uses the
[OHIF UI customization service](../../platform/services/ui/customization-service.md) to
instantiate the `BaseDataSourceConfigurationAPI` instance to configure a data source.
A UI configurable data source should have a `configurationAPI` field as part of
its `configuration` in the OHIF config file. The `configurationAPI` value is the
customization id of the customization module that provides the factory method
to instantiate the `BaseDataSourceConfigurationAPI` instance.
For example, the following is a snippet of a Google Cloud Healthcare data source configuration.
```js
dataSources: [
{
namespace: '@ohif/extension-default.dataSourcesModule.dicomweb',
sourceName: 'google-dicomweb',
configuration: {
name: 'GCP',
wadoUriRoot: 'https://healthcare.googleapis.com/v1/projects/ohif-cloud-healthcare/locations/us-east4/...',
...
configurationAPI: 'ohif.dataSourceConfigurationAPI.google',
...
},
},
]
```
This suggests that the factory method is provided by the `'ohif.dataSourceConfigurationAPI.google'`
customization module. That customization module is provided by the `default` extension's
`getCustomizationModule` and looks something like the following snippet of code. Notice that
the factory method's name MUST be `factory` and accept one argument - the data source name.
Furthermore note how the constructor is invoked with anything required by the concrete configuration
API class.
```js
export default function getCustomizationModule({
servicesManager,
extensionManager,
}) {
return [
{
name: 'default',
value: [
{
// The factory for creating an instance of a BaseDataSourceConfigurationAPI for Google Cloud Healthcare
id: 'ohif.dataSourceConfigurationAPI.google',
factory: (dataSourceName: string) =>
new GoogleCloudDataSourceConfigurationAPI(
dataSourceName,
servicesManager,
extensionManager
),
},
],
},
];
}
```

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---
sidebar_position: 3
sidebar_label: DICOM JSON
---
# DICOM JSON
You can launch the OHIF Viewer with a JSON file which points to a DICOMWeb
server as well as a list of study and series instance UIDs along with metadata.
An example would look like
`https://viewer.ohif.org/viewer/dicomjson?url=https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001.json`
As you can see the url to the location of the JSON file is passed in the query
after the `dicomjson` string, which is
`https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001.json` (this
json file has been generated by OHIF team and stored in an amazon s3 bucket for
the purpose of the guide).
## DICOM JSON sample
Here we are using the LIDC-IDRI-0001 case which is a sample of the LIDC-IDRI
dataset. Let's have a look at the JSON file:
### Metadata
JSON file stores the metadata for the study level, series level and instance
level. A JSON launch file should follow the same structure as the one below.
:::tip
You can use our script to generate the JSON file from a hosted endpoint. See
`.scripts/dicom-json-generator.js`
You could run it like this:
```bash
node .scripts/dicom-json-generator.js '/path/to/study/folder' 'url/to/dicom/server/folder' 'json/output/file.json'
```
Some modalities require additional metadata to be added to the JSON file. You can read more about the minimum amount of metadata required for the viewer to work [here](../../faq.md#what-are-the-list-of-required-metadata-for-the-ohif-viewer-to-work). We will handle this in the script. For example, the script will add the CodeSequences for SR in order to display the measurements in the viewer.
:::
Note that at the instance level metadata we are storing both the `metadata` and
also the `url` for the dicom file on the dicom server. In this case we are
referring to
`dicomweb:https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001/01-01-2000-30178/3000566.000000-03192/1-001.dcm`
which is stored in another directory in our s3. (You can actually try
downloading the dicom file by opening the url in your browser).
The URL to the script in the given example is `https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001/01-01-2000-30178`. This URL serves as the parent directory that contains all the series within their respective folders.
```json
{
"studies": [
// first study metadata
{
"StudyInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.298806137288633453246975630178",
"StudyDate": "20000101",
"StudyTime": "",
"PatientName": "",
"PatientID": "LIDC-IDRI-0001",
"AccessionNumber": "",
"PatientAge": "",
"PatientSex": "",
"series": [
// first series metadata
{
"SeriesInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.179049373636438705059720603192",
"SeriesNumber": 3000566,
"Modality": "CT",
"SliceThickness": 2.5,
"instances": [
// first instance metadata
{
"metadata": {
"Columns": 512,
"Rows": 512,
"InstanceNumber": 1,
"SOPClassUID": "1.2.840.10008.5.1.4.1.1.2",
"PhotometricInterpretation": "MONOCHROME2",
"BitsAllocated": 16,
"BitsStored": 16,
"PixelRepresentation": 1,
"SamplesPerPixel": 1,
"PixelSpacing": [0.703125, 0.703125],
"HighBit": 15,
"ImageOrientationPatient": [1, 0, 0, 0, 1, 0],
"ImagePositionPatient": [-166, -171.699997, -10],
"FrameOfReferenceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.229925374658226729607867499499",
"ImageType": ["ORIGINAL", "PRIMARY", "AXIAL"],
"Modality": "CT",
"SOPInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.262721256650280657946440242654",
"SeriesInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.179049373636438705059720603192",
"StudyInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.298806137288633453246975630178",
"WindowCenter": -600,
"WindowWidth": 1600,
"SeriesDate": "20000101"
},
"url": "dicomweb:https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001/01-01-2000-30178/3000566.000000-03192/1-001.dcm"
},
// second instance metadata
{
"metadata": {
"Columns": 512,
"Rows": 512,
"InstanceNumber": 2,
"SOPClassUID": "1.2.840.10008.5.1.4.1.1.2",
"PhotometricInterpretation": "MONOCHROME2",
"BitsAllocated": 16,
"BitsStored": 16,
"PixelRepresentation": 1,
"SamplesPerPixel": 1,
"PixelSpacing": [0.703125, 0.703125],
"HighBit": 15,
"ImageOrientationPatient": [1, 0, 0, 0, 1, 0],
"ImagePositionPatient": [-166, -171.699997, -12.5],
"FrameOfReferenceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.229925374658226729607867499499",
"ImageType": ["ORIGINAL", "PRIMARY", "AXIAL"],
"Modality": "CT",
"SOPInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.512235483218154065970649917292",
"SeriesInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.179049373636438705059720603192",
"StudyInstanceUID": "1.3.6.1.4.1.14519.5.2.1.6279.6001.298806137288633453246975630178",
"WindowCenter": -600,
"WindowWidth": 1600,
"SeriesDate": "20000101"
},
"url": "dicomweb:https://ohif-dicom-json-example.s3.amazonaws.com/LIDC-IDRI-0001/01-01-2000-30178/3000566.000000-03192/1-002.dcm"
}
// ..... other instances metadata
]
}
// ... other series metadata
],
"NumInstances": 133,
"Modalities": "CT"
}
// second study metadata
]
}
```
![](../../assets/img/dicom-json.png)
### Local Demo
You can run OHIF with a JSON data source against you local datasets (given that
their JSON metadata is extracted).
First you need to put the JSON file and the folder containing the dicom files
inside your `public` folder. Since files are served from your local server the
`url` for the JSON file will be `http://localhost:3000/LIDC-IDRI-0001.json` and
the dicom files will be
`dicomweb:http://localhost:3000/LIDC-IDRI-0001/01-01-2000-30178/3000566.000000-03192/1-001.dcm`.
After `yarn install` and running `yarn dev` and opening the browser at
`http://localhost:3000/viewer/dicomjson?url=http://localhost:3000/LIDC-IDRI-0001.json`
will display the viewer.
Download JSON file from
[here](https://www.dropbox.com/sh/zvkv6mrhpdze67x/AADLGK46WuforD2LopP99gFXa?dl=0)
Sample DICOM files can be downloaded from
[TCIA](https://wiki.cancerimagingarchive.net/display/Public/LIDC-IDRI) or
directly from
[here](https://www.dropbox.com/sh/zvkv6mrhpdze67x/AADLGK46WuforD2LopP99gFXa?dl=0)
Your public folder should look like this:
![](../../assets/img/dicom-json-public.png)
:::tip
It is important to URL encode the `url` query parameter especially if the `url`
parameter itself also contains query parameters. So for example,
`http://localhost:3000/viewer/dicomjson?url=http://localhost:3000/LIDC-IDRI-0001.json?key0=val0&key1=val1`
should be...
`http://localhost:3000/viewer/dicomjson?url=http://localhost:3000/LIDC-IDRI-0001.json?key0=val0%26key1=val1`
Notice the ampersand (`&`) is encoded as `%26`.
:::
:::note
When hosting the DICOM JSON files, it is important to be aware that certain providers
do not automatically handle the 404 error and fallback to index.html. For example, Netlify
handles this, but Azure does not. Consequently, when you attempt to access a link with a
specific URL, a 404 error will be displayed.
This issue also occurs locally, where the http-server does not handle it. However,
if you utilize the `serve` package (npx serve ./dist -c ../public/serve.json), it effectively addresses this problem.
:::

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---
sidebar_position: 4
sidebar_label: DICOMweb Proxy
---
# DICOMweb Proxy
You can launch the OHIF Viewer with a url that returns a JSON file which
contains a DICOMWeb configuration. The DICOMweb Proxy constructs a DICOMweb
datasource and delegates subsequent requests for metadata and images to that.
Usage is similar to that of the [DICOM JSON](./dicom-json.md) datasource and
might look like
`https://viewer.ohif.org/viewer/dicomwebproxy?url=https://ohif-dicom-json-example.s3.amazonaws.com/dicomweb.json`
The url to the location of the JSON file is passed in the query
after the `dicomwebproxy` string, which is
`https://ohif-dicom-json-example.s3.amazonaws.com/dicomweb.json` (this json file
does not exist at the moment of this writing).
## DICOMweb JSON configuration sample
The json returned by the url in this example contains a dicomweb configuration
(see [DICOMweb](dicom-web.md)), in a "servers" object, which is then used to
construct a dynamic DICOMweb datasource to delegate requests to. Here is an
example configuration that might be returned using the url parameter.
```json
{
"servers": {
"dicomWeb": [
{
"name": "DCM4CHEE",
"wadoUriRoot": "https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/wado",
"qidoRoot": "https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/rs",
"wadoRoot": "https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/rs",
"qidoSupportsIncludeField": true,
"supportsReject": true,
"imageRendering": "wadors",
"thumbnailRendering": "wadors",
"enableStudyLazyLoad": true,
"supportsFuzzyMatching": true,
"supportsWildcard": true
}
]
}
}
```
The DICOMweb Proxy expects the json returned by the url parameter it is invoked
with to include a servers object which contains a "dicomWeb" configuration array
as above. It will only consider the first array item in the dicomWeb
configuration.

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---
sidebar_position: 2
sidebar_label: DICOMweb
---
# DICOMweb
## Set up a local DICOM server
ATTENTION! Already have a remote or local server? Skip to the
[configuration section](#configuration-learn-more) below.
While the OHIF Viewer can work with any data source, the easiest to configure
are the ones that follow the [DICOMWeb][dicom-web] spec.
1. Choose and install an Image Archive
2. Upload data to your archive (e.g. with DCMTK's [storescu][storescu] or your
archive's web interface)
3. Keep the server running
For our purposes, we will be using `Orthanc`, but you can see a list of
[other Open Source options](#open-source-dicom-image-archives) below.
### Requirements
- Docker
- [Docker for Mac](https://docs.docker.com/docker-for-mac/)
- [Docker for Windows (recommended)](https://docs.docker.com/docker-for-windows/)
- [Docker Toolbox for Windows](https://docs.docker.com/toolbox/toolbox_install_windows/)
_Not sure if you have `docker` installed already? Try running `docker --version`
in command prompt or terminal_
> If you are using `Docker Toolbox` you need to change the _PROXY_DOMAIN_
> parameter in _platform/app/package.json_ to http://192.168.99.100:8042 or
> the ip docker-machine ip throws. This is the value [`WebPack`][webpack-proxy]
> uses to proxy requests
## Open Source DICOM Image Archives
There are a lot of options available to you to use as a local DICOM server. Here
are some of the more popular ones:
| Archive | Installation |
| --------------------------------------------- | ---------------------------------- |
| [DCM4CHEE Archive 5.x][dcm4chee] | [W/ Docker][dcm4chee-docker] |
| [Orthanc][orthanc] | [W/ Docker][orthanc-docker] |
| [DICOMcloud][dicomcloud] (**DICOM Web only**) | [Installation][dicomcloud-install] |
| [OsiriX][osirix] (**Mac OSX only**) | Desktop Client |
| [Horos][horos] (**Mac OSX only**) | Desktop Client |
_Feel free to make a Pull Request if you want to add to this list._
Below, we will focus on `DCM4CHEE` and `Orthanc` usage:
### Running Orthanc
_Start Orthanc:_
```bash
# Runs orthanc so long as window remains open
yarn run orthanc:up
```
_Upload your first Study:_
1. Navigate to
[Orthanc's web interface](http://localhost:8042/app/explorer.html) at
`http://localhost:8042/app/explorer.html` in a web browser.
2. In the top right corner, click "Upload"
3. Click "Select files to upload..." and select one or more DICOM files
4. Click "Start the upload"
#### Orthanc: Learn More
You can see the `docker-compose.yml` file this command runs at
[`<project-root>/platform/app/.recipes/Nginx-Orthanc`][orthanc-docker-compose], and more on
Orthanc for Docker in [Orthanc's documentation][orthanc-docker].
#### Connecting to Orthanc
Now that we have a local Orthanc instance up and running, we need to configure
our web application to connect to it. Open a new terminal window, navigate to
this repository's root directory, and run:
```bash
# If you haven't already, enable yarn workspaces
yarn config set workspaces-experimental true
# Restore dependencies
yarn install
# Run our dev command, but with the local orthanc config
yarn run dev:orthanc
```
#### Configuration: Learn More
> For more configuration fun, check out the
> [Essentials Configuration](../index.md) guide.
Let's take a look at what's going on under the hood here. `yarn run dev:orthanc`
is running the `dev:orthanc` script in our project's `package.json` (inside
`platform/app`). That script is:
```js
cross-env NODE_ENV=development PROXY_TARGET=/dicom-web PROXY_DOMAIN=http://localhost:8042 APP_CONFIG=config/docker_nginx-orthanc.js webpack-dev-server --config .webpack/webpack.pwa.js -w
```
- `cross-env` sets three environment variables
- PROXY_TARGET: `/dicom-web`
- PROXY_DOMAIN: `http://localhost:8042`
- APP_CONFIG: `config/docker_nginx-orthanc.js`
- `webpack-dev-server` runs using the `.webpack/webpack.pwa.js` configuration
file. It will watch for changes and update as we develop.
`PROXY_TARGET` and `PROXY_DOMAIN` tell our development server to proxy requests
to `Orthanc`. This allows us to bypass CORS issues that normally occur when
requesting resources that live at a different domain.
The `APP_CONFIG` value tells our app which file to load on to `window.config`.
By default, our app uses the file at
`<project-root>/platform/app/public/config/default.js`. Here is what that
configuration looks like:
```js
window.config = {
routerBasename: '/',
extensions: [],
modes: [],
showStudyList: true,
dataSources: [
{
namespace: '@ohif/extension-default.dataSourcesModule.dicomweb',
sourceName: 'dicomweb',
configuration: {
friendlyName: 'dcmjs DICOMWeb Server',
name: 'DCM4CHEE',
wadoUriRoot: 'https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/wado',
qidoRoot: 'https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/rs',
wadoRoot: 'https://server.dcmjs.org/dcm4chee-arc/aets/DCM4CHEE/rs',
qidoSupportsIncludeField: true,
supportsReject: true,
imageRendering: 'wadors',
thumbnailRendering: 'wadors',
enableStudyLazyLoad: true,
supportsFuzzyMatching: true,
supportsWildcard: true,
},
},
],
defaultDataSourceName: 'dicomweb',
};
```
### Data Source Configuration Options
The following properties can be added to the `configuration` property of each data source.
##### `dicomUploadEnabled`
A boolean indicating if the DICOM upload to the data source is permitted/accepted or not. A value of true provides a link on the OHIF work list page that allows for DICOM files from the local file system to be uploaded to the data source
:::tip
The [OHIF plugin for Orthanc](https://book.orthanc-server.com/plugins/ohif.html) by default utilizes the DICOM JSON data
source and it has been discovered that only those studies uploaded to Orthanc AFTER the plugin has been installed are
available as DICOM JSON. As such, if the OHIF plugin for Orthanc is desired for studies uploaded prior to installing the plugin,
then consider switching to using [DICOMweb instead](https://book.orthanc-server.com/plugins/ohif.html#using-dicomweb).
:::
![toolbarModule-layout](../../assets/img/uploader.gif)
#### `singlepart`
A comma delimited string specifying which payloads the data source responds with as single part. Those not listed are considered multipart. Values that can be included here are `pdf`, `video`, `bulkdata`, `thumbnail` and `image`.
For DICOM video and PDF it has been found that Orthanc delivers multipart, while DCM4CHEE delivers single part. Consult the DICOM conformance statement for your particular data source to determine which payload types it delivers.
To learn more about how you can configure the OHIF Viewer, check out our
[Configuration Guide](../index.md).
### DICOM Upload
See the [`dicomUploadEnabled`](#dicomuploadenabled) data source configuration option.
### DICOM PDF
See the [`singlepart`](#singlepart) data source configuration option.
### DICOM Video
See the [`singlepart`](#singlepart) data source configuration option.
### BulkDataURI
The `bulkDataURI` configuration option allows the datasource to use the
bulkdata end points for retrieving metadata if originally was not included in the
response from the server. This is useful for the metadata information that
are big and can/should be retrieved in a separate request. In case the bulkData URI
is relative (instead of absolute) the `relativeResolution` option can be used to
specify the resolution of the relative URI. The possible values are `studies`, `series` and `instances`.
Certainly the knowledge of how the server is configured is required to use this option.
```js
bulkDataURI: {
enabled: true,
relativeResolution: 'series',
},
```
### Running DCM4CHEE
dcm4che is a collection of open source applications for healthcare enterprise
written in Java programming language which implements DICOM standard. dcm4chee
(extra 'e' at the end) is dcm4che project for an Image Manager/Image Archive
which provides storage, retrieval and other functionalities. You can read more
about dcm4chee in their website [here](https://www.dcm4che.org/)
DCM4chee installation is out of scope for these tutorials and can be found
[here](https://github.com/dcm4che/dcm4chee-arc-light/wiki/Run-minimum-set-of-archive-services-on-a-single-host)
An overview of steps for running OHIF Viewer using a local DCM4CHEE is shown
below:
<div style={{padding:"56.25% 0 0 0", position:"relative"}}>
<iframe src="https://player.vimeo.com/video/843233881?badge=0&amp;autopause=0&amp;player_id=0&amp;app_id=58479" frameBorder="0" allow="autoplay; fullscreen; picture-in-picture" allowFullScreen style= {{ position:"absolute",top:0,left:0,width:"100%",height:"100%"}} title="measurement-report"></iframe>
</div>
[dcm4chee]: https://github.com/dcm4che/dcm4chee-arc-light
[dcm4chee-docker]:
https://github.com/dcm4che/dcm4chee-arc-light/wiki/Running-on-Docker
[orthanc]: https://www.orthanc-server.com/
[orthanc-docker]: http://book.orthanc-server.com/users/docker.html
[dicomcloud]: https://github.com/DICOMcloud/DICOMcloud
[dicomcloud-install]: https://github.com/DICOMcloud/DICOMcloud#running-the-code
[osirix]: http://www.osirix-viewer.com/
[horos]: https://www.horosproject.org/
[default-config]:
https://github.com/OHIF/Viewers/blob/master/platform/app/public/config/default.js
[html-templates]:
https://github.com/OHIF/Viewers/tree/master/platform/app/public/html-templates
[config-files]:
https://github.com/OHIF/Viewers/tree/master/platform/app/public/config
[storescu]: http://support.dcmtk.org/docs/storescu.html
[webpack-proxy]: https://webpack.js.org/configuration/dev-server/#devserverproxy

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---
sidebar_position: 1
sidebar_label: Introduction
---
# Data Source
The internal data structure of OHIF’s metadata follows naturalized DICOM JSON, a
format pioneered by `dcmjs`. In short DICOM metadata headers with DICOM Keywords
instead of tags and sequences as arrays, for easy development and clear code.
Here in this section we will discuss couple of data sources that are commonly used
and OHIF has provided the implementation for them.
## Custom Data Source
Do you have a custom data source? or a custom data that you want to use in OHIF?
You can easily write a data source to map your data to OHIF’s native format.
You can read more in the [Data Source Module](../../platform/extensions/modules/data-source.md)

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---
sidebar_position: 5
sidebar_label: Static Files
---
# Static Files
There is a binary DICOM to static file generator, which provides easily served
binary files. The files are all compressed in order to reduce space
significantly, and are pre-computed for the files required for OHIF, so that the
performance of serving the files is just the read from disk/write to http stream
time, without any extra processing time.
The project for the static wado files is located here: [static-wado]:
https://github.com/OHIF/static-wado
It can be compiled with Java and Gradle, and then run against a set of dicom, in
the example located in /dicom/study1 outputting to /dicomweb, and then a server
run against that data, like this:
```bash
git clone https://github.com/OHIF/static-wado
cd static-wado
./gradlew installDist
StaticWado/build/install/StaticWado/bin/StaticWado -d /dicomweb /dicom/study1
cd /dicomweb
npx http-server -p 5000 --cors -g
# you can use npx serve ./dist -l 8080 -c ../public/serve.json as an alternative to http-server
```
There is then a dev environment in the platform/app directory which can be
run against those files, like this:
```
cd platform/app
yarn dev:static
```
Additional studies can be added to the dicomweb by re-running the StaticWado
command. It will create a single studies.gz index file (JSON DICOM file,
compressed) containing an index of all studies created. There is then a small
extension to OHIF which performs client side indexing.
The StaticWado command also knows how to deploy a client and dicomweb directory
to Amazon s3, which can then server files up directly. There is another build
setup build:aws in the viewer package.json to create such a deployment.