JavaScript client implementation of DICOMweb.
For further details please refer to PS3.18 of the DICOM standard.
This is work-in-progress and should not be used in clinical practice.
The main motivation for this project is:
- Support for storing, quering, retrieving DICOM objects over the web using RESTful services STOW-RS, QIDO-RS and WADO-RS, respectively
- Building a lightweight library to facilitate integration into web applications
Install the dicomweb-client package using the npm
package manager:
npm install dicomweb-client
Build and test code locally:
git clone https://github.com/dcmjs-org/dicomweb-client ~/dicomweb-client
cd ~/dicomweb-client
npm install
npm run build
npm test
<script type="text/javascript" src="https://unpkg.com/dicomweb-client"></script>
const url = 'http://localhost:8080/dicomweb';
const client = new DICOMwebClient.api.DICOMwebClient({url});
client.searchForStudies().then(studies => {
console.log(studies)
});
Use semantic
commit messages to generate releases and change log entries: Semantic Release: How does it work?
Please cite the following article when using the client for scientific studies: Herrmann et al. J Path Inform. 2018:
@article{jpathinform-2018-9-37,
Author={
Herrmann, M. D. and Clunie, D. A. and Fedorov A. and Doyle, S. W. and Pieper, S. and
Klepeis, V. and Le, L. P. and Mutter, G. L. and Milstone, D. S. and Schultz, T. J. and
Kikinis, R. and Kotecha, G. K. and Hwang, D. H. and Andriole, K, P. and Iafrate, A. J. and
Brink, J. A. and Boland, G. W. and Dreyer, K. J. and Michalski, M. and
Golden, J. A. and Louis, D. N. and Lennerz, J. K.
},
Title={Implementing the {DICOM} standard for digital pathology},
Journal={Journal of Pathology Informatics},
Year={2018},
Number={1},
Volume={9},
Number={37}
}
The developers gratefully acknowledge their reseach support:
- Open Health Imaging Foundation (OHIF)
- Quantitative Image Informatics for Cancer Research (QIICR)
- Radiomics
- The Neuroimage Analysis Center
- The National Center for Image Guided Therapy
- The MGH & BWH Center for Clinical Data Science