Features

Flexible Structure

The datasets are presented in a searchable list instead of predefined project structure.

Semantic Search

Use the semantic search to find datasets you need.

Organize and Sharing

Create folders and produce a data structure you like. Share it and collaborate.

Controlled Access

Choose the access level for each dataset individually.

Application Ready

Use the full featured API to connect to the repository from your software.

Standard File Formats

DICOM, ITK images, CDISC, STL, Statismo and ontology based meta-data.

Our Competences

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

Anonymisation of patient information and image features like face soft tissue.

Data Storage

Certified, efficient, and innovative data center based in Switzerland.

Research expertise

Sound expertise and broad experience in research support and collaboration management.

Acquisition

Acquisition of high quality image data and curation by experts.

Controlled

Controlled distribution of medical image data.

Anatomy

Anatomy based search to find the correct images.

Get Started

With the Website

Upload

Go the to the Upload Page and add a dataset to the upload queue

View

Unpublished Data

After upload, your dataset is listed on the unpublished page

View

Modifiy Meta-Data

Add value to your data by adding meta-data

View

Publish

Follow the steps and set meta-info, permission and related data to publish the data

View

Published Data

After uploading and publishing your dataset is listed on the published data page

View

Search For Data

Use -Symbol (@Body) to find anatomical structures

View

Organize by Folder

Copy data into your folder structure

View

Download a Folder

Select the folder to retrieve your collected data

View

With the API

Please consider developing on the demo (https://demo.smir.ch) server before you interact with the live system.

API Reference Python 3 API Connector Scala (JAVA) API Connector

Chunked file upload

Python code

## import libs
from pathlib import Path
from vsdConnect import connect
## connect to demo
api = connect.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)

Console output

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

Download a folder

Python code

from pathlib import Path
from vsdConnect import connect

# connect to the demo API
api = connectVSD.VSDConnecter()
## search for the test folder and retrieve the folder object
folder = api.getFolderByName('One')
for obje in folder.containedObjects:
    ## get each object in the folder
    obj = api.getObject(obje.selfUrl)
    ## Download directory
    home_dir = Path('/Home/User/Downloads')
    obj.download(api, working_dir=home_dir,)

News

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Institutions using SMIR