A utilities library to download, archive and transfer DICOM images from PACS systems. Accompanies dcm4che-docker, a distributed dcm4chee service run on Docker Swarm
This repository contains utilities for DICOM image related operations for Team Kaiser. These include:
- Download DICOM(s) from Clinical Data Manager system.
- Archive DICOM data from multiple studies for deserialized transfer over networks.
- Convert DICOM(s) into a Raster file format (JPEG, PNG, BMP)
General requirements include:
python3.5+
pip version 9.0.3 or higher
pydicom
opencv-python
dicom2nifti
dicomweb-client
progressbar
Before running these scripts, be sure to install all required packages by running:
pip3 install -r requirements.txt
Make sure you have the read and write permissions to the folder(s) that contain the DICOM files.
python3 utils/executeDicom.py [dest] [studyid_file] [url]
Options:
dest: The path to where you want to create the dicoms folder.
studyid_file: The text file contains all study instance UIDs of the studies you want to download.
url: The address of server where you want to download dicoms from.
This must include 'aets/DCM4CHEE'(see example usage below)
--zip or -z: if you want to zip the dicoms folder.
This will clean up the downloaded files to eliminate duplicates.
Example usage:
python3 utils/executeDicom.py /users/home/data studyid.txt http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE
With zipping:
python3 utils/executeDicom.py /users/home/data studyid.txt http://localhost:8080/dcm4chee-arc/aets/DCM4CHEE --zip
The study_list contains ohifid.txt, that contains a few studies on dcm4chee server of dcmjs.
Running executeDicom.py create a folder named dicoms at dest. Below is the folder structure of dicoms:
.
├── ...
├── dicoms # dicoms folder contains study folder
│ ├── ...
│ ├── study1 # study folders are named by their study instance UID.
│ │ ├── 0.dcm # all DICOM(s)
│ │ ├── 1.dcm
│ │ ├── 2.dcm
│ │ ├── ...
│ ├── study2
│ │ ├── 0.dcm
│ │ ├── 1.dcm
│ │ ├── 2.dcm
│ │ ├── ...
│ └── ...
├── dicoms.zip # The existence of this file depends on wether you choose to zip the dicoms folder or not
└── ...
python3 utils/dicomConverter.py [src] [dest] [file_format]
Options:
src: The path to the dicoms folder, the structure should be same as the one above.
dest_folder: The path to where you want to create the Clara_Structure folder.
file_format: The format to be converted into. Ex: JPEG, PNG, BMP
Flags: -q or --quiet: Set the logger to only print warnings to STDOUT.
python3 utils/executeStruct.py [src] [dest] [file_format]
Options:
src: The path to the dicoms folder, the structure should be same as the one above.
dest: The path to where you want to create the Clara_Structure folder.
file_format: The format to be converted into. Ex: JPEG, PNG, BMP
Example usage:
python3 utils/executeStruct.py /users/home/data /users/home/converted_data JPEG
Running executeStruct.py create a folder named Clara_Structure at dest. Below is the folder structure of Clara_Structure:
.
├── ...
├── Clara_Structure # Clara_Structure folder contains study folder
│ ├── ...
│ ├── study1 # study folders are named by their study instance UID.
│ │ ├── dataset_root # dataset_root folder contains the folder structure for Clara traning.
│ │ │ ├── png_file # png_file folder contains all converted PNG file.
│ │ │ ├── 0.png # all PNG(s)
│ │ │ ├── 1.png
│ │ │ ├── 2.png
│ │ │ ├── ...
│ ├── study2
│ │ ├── dataset_root
│ │ │ ├── png_file
│ │ │ ├── 0.png
│ │ │ ├── 1.png
│ │ │ ├── 2.png
│ │ │ ├── ...
│ └── ...
└── ...
python3 utils/uploadDicom.py [server] [port] [src]
Options:
server: The host IP address of the dcm4chee server.
port: The port of the AE title 'DCM4CHEE'.
src: The path to the dicoms folder or dicoms zip file.
Example usage:
python3 utils/uploadDicom.py localhost 11112 dicoms.zip
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