Raccoon is a noSQL-based medical image archive for managing the DICOM images is primarily maintained by the Imaging Informatics Labs. It uses the MongoDB to manage the DICOM images and provide RESTful API, supported both FHIR ImagingStudy and DICOMweb to store, query/retrieve, and manage DICOM images. Raccoon is bulit on the top of the Burni FHIR Server to manage the FHIR resourcs related to medical images
- Before starting Raccoon, MongoDB, imagemagick must be installed.
- This project uses the submodule with BlueLight for DICOM viewer. If you want to use it, run
git submodule initandgit submodule updatewhen the first time. - Node.js >= 14
- Python >= 3.7
You can follow this Full Installation Guide 🎉
The guide above has every detailed installation step for each required software
😄 It's extremely friendly for newbie 😄
The guide above has every detailed installation step for each required software
😄 It's extremely friendly for newbie 😄
- Windows 10 64bits
- MongoDB > 4.0
- Anaconda
- GDCM enviroment in Anaconda
- imagemagick
- Go to project root path and run:
npm install
npm run build #This will download dcmtk executable binaries to ./models/dcmtk and generate example dotenv file.
Windows installation ends here, scroll down to see Configuration & Deploy guide
- Ubuntu v20.4
- MongoDB > 4.0
- GDCM
sudo api-get install python3-gdcm libgdcm3.0
- imagemagick
sudo apt-get install imagemagick #ubuntu
- Go to project root path and run:
npm install
npm run build #This will download dcmtk using apt-get install and generate example dotenv file.- The
.envfile at project root. - You can copy the
.env.templateand modify it.
ENV='windows' #input the os type. enum: windows , linux
MONGODB_NAME="Raccoon"
MONGODB_HOSTS=["mongodb"]
MONGODB_PORTS=[27017]
MONGODB_USER="user"
MONGODB_PASSWORD="password"
MONGODB_SLAVEMODE=false
SERVER_HOST="localhost"
SERVER_PORT=8081
DICOM_STORE_ROOTPATH="C:/" #The root path that DICOMweb STOW to store
DICOMWEB_HOST="localhost"
DICOMWEB_PORT=8081
DICOMWEB_API="dicom-web"
FHIRSERVER_APIPATH="api/fhir"
FHIRSERVER_HOST="localhost"
FHIRSERVER_PORT=8081
FHIR_NEED_PARSE_PATIENT=true #STOW will generate Patient data using DICOMTag. If you want custom FHIR patient , please change to false.
USE_CONDA=false
CONDA_PATH="C:\\Users\\chinHPlaptop\\anaconda3\\Scripts\\conda.exe"
CONDA_GDCM_ENV_NAME="gdcm"
USE_DCM2JPEG_PYTHONAPI=true
DCM2JPEG_PYTHONAPI_PORT=5000
ENABLE_LOGIN_ACCESS=false- Config path :
public/scripts/config.js - Change all hostname and port with your server config.
var envConfig = {
QIDO : {
hostName :'127.0.0.1' ,
port : '9090' ,
api : 'dicom-web' ,
http : "http" //http or https
} ,
WADO : {
hostName : '127.0.0.1' ,
port : '9090' ,
api : 'dicom-web' ,
http : "http"
} ,
FHIR : {
hostName : '127.0.0.1' ,
port : '9090' ,
api : 'api/fhir' ,
http : "http"
}
}- A simple web-based user interface is provided to manage the DICOM objects in Raccoon.
- For DICOMWeb client, Raccoon can integrate with BlueLight, a lightweight Web-based DICOM Viewer.
node server- The docker-compose example already in project root path.
Example:
version: '3.4'
services:
mongodb:
image: mongo:4.2
container_name : mongodb
restart: always
ports:
- 27017:27017
volumes:
- ./mongodb/db:/data/db
environment:
# provide your credentials here
- MONGO_INITDB_DATABASE=admin
- MONGO_INITDB_ROOT_USERNAME=root
- MONGO_INITDB_ROOT_PASSWORD=Raccoon#Admin2Mongo
- MONGO_PORT=27017
raccoon:
build:
context : ./
dockerfile : Dockerfile
container_name: raccoon
command: >
/bin/sh -c '
while ! nc -z mongodb 27017;
do
echo "waiting for database ...";
sleep 3;
done;
echo "db is ready!";
npm install;
pm2-runtime start ecosystem.config.js --node-args="--max-old-space-size=4096";
'
volumes :
- ./:/nodejs/raccoon
- ./raccoon-storage:/dicomFiles
- ./raccoon-null/node_modules:/nodejs/raccoon/node_modules
- ./raccoon-null/build:/nodejs/raccoon/build
- ./raccoon-null/models:/nodejs/raccoon/models/dcmtk/linux-lib
ports:
- 8081:8081
depends_on:
- mongodb
tty : true
restart: on-failure:3
stdin_open : truedocker-compose up -dQIDO-RS、WADO-RS、STOW-RS : /dicom-web/studies
WADO-URI : /api/dicom/wado
base : /api/fhir/{resource}
metadata : /api/fhir/metadata
- Raccoon支援DICOMWeb標準傳輸協定，包含QIDO-RS, WADO-RS, WADO-URI, STOW等。
- 支援各種Transfer Syntax 以及SOP Class影像
- 通過台灣醫學資訊聯測 MI-TW 2020 - 項目: Track #4 - 醫學影像影像 DICOMWeb Query/Retrieve Source
- 通過台灣醫學資訊聯測 MI-TW 2021 - 項目: Track #6 - 數位病理影像 DICOMWeb Query/Retrieve Source
- JSON Web Token(JWT) authentication
- ID/Password login
- Raccoon supports the following DICOMWeb API
- metadata (JSON)
- QIDO-RS: (JSON)
- WAOD-RS
- WADO-URI: supported both: DICOM and JPEG
- STOW-RS
- Raccoon can act a FHIR server supporting the following FHIR resources and FHIR API which can be found in FHIR metadata services
- patient
- organization
- ImagingStudy
- endpoint
- Note: Raccoon is focused on medical imaging-related resources, not all FHIR resources, built on the top of the Simple-Express-FHIR-Server. If you are interesting in FHIR soultion, please visit Simple-Express-FHIR-Server.
- General image storages, e.g., CT, MR, X-ray, etc.
- Multiframe Image Storage - partical support
- Specifal SOP Class: VL Microscopic Image Storage: DICOM WSI
- GSPS, Segementation, SR, etc.
- Supplement 222: Whole Slide Microscopy Bulk Annotations Storage SOP Class
- Raccoon DICOM Server uses several open source libraries as following:
- fhir-mongoose-schema-generator. It can generate the collection's schema in MongoDB from mapping to FHIR resources used in Raccoon automatically.
- Raccoon provides a tool to convert DICOM objects included in a study to a FHIR ImagingStudy resources stored as a MononDB document.
- We hava another FHIR Server, is designed to creating a tiny FHIR server supported specified FHIR resources.
- Dockerize
- DICOM Protocol: C-ECHO SCP, C-STORE SCP, C-MOVE SCP.
- IHE Invoke Image Display (IID) Profile [RAD-106]
- DICOM Supplement 219 - JSON Representation of DICOM Structured Reports. Referenced standard: DICOM Sup 219
- Write a new proposal of FHIR Implementation Guide of Raccoon modified from FHIR ImagingStudy Core Resource which lacks many tags commonly used in PACS.
- This project is supported by a grant from the Ministry of Science and Technology Taiwan.
- Thanks 琦雯Queenie, Queenie's github for contributing the logo design.