Storing medical image data requires special knowledge. SICAS offers a unique combination of competence in acquiring and storing medical images, in processing and visualising data for research and applications in medicine.
Anonymisation of patient information and image features like face soft tissue.
Certified, efficient, and innovative data center based in Switzerland.
Sound expertise and broad experience in research support and collaboration management.
Acquisition of high quality image data and curation by experts.
Controlled distribution of medical image data.
Anatomy based search to find the correct images.
Please consider developing on the demo (https://demo.smir.ch) server before you interact with the live system.
## import libs from pathlib import Path import connectVSD ## connect to demo api = connectVSD.VSDConnecter() ## define filepath fp = Path('C:' + os.sep, 'test', 'test.nii') ## Define chunk size to eg. 8 MB if you dont want to use the default 4MB chunk = 1024 * 4096 * 2 ## upload using the chunkFileUpload obj = api.chunkFileUpload(fp, chunksize = chunk) ## print the selfUrl of the generated object print(obj.selfUrl)
uploading part 1 of 3 uploaded part 1 of 3 uploading part 2 of 3 uploaded part 2 of 3 uploading part 3 of 3 uploaded part 3 of 3 https://demo.smir.ch/api/objects/1
from pathlib import Path import connectVSD # connect to the demo API api = connectVSD.VSDConnecter() ## search for the test folder and retrieve the folder object folder = api.getFolderByName('test') for obje in folder.containedObjects: ## get each object in the folder obj = api.getObject(obje['selfUrl']) ## define the filepath of the downloaded file fp = Path(obj.name).with_suffix('.zip') ## download the file api.downloadZip(obj.downloadUrl, fp)