The INCISIVE platform accepts imaging data (MRI, US, CT, PET-CT, Mammography, radiography and histopathological images) for 4 types of cancer e.g., breast, colorectal, prostate and lung cancer as DICOM or NIfTi files. Also, it accepts de-identified clinical metadata related to the imaging data as excel files (.xls) following a specific template.

If you represent an organization or an individual who can legally share health data, you can register on the INCISIVE platform and become a member of the data sharing community. Fill-in the contact form you can find on this page and our representatives will get in touch with you with further instructions.

Once your registration process is complete, our team will guide you in setting-up/configuring your instance of the INCISIVE platform. Our platform offers two set-up options: federated or centralised data storage, based on your preference (see How can I share my data? below). After that you will have access to the INCISIVE platform where you can share your data.

If you share data during the INCISIVE lifetime (i.e., until March 2024), the data will be used by the AI developers working in the INCISIVE project for the training and validation of AI Solutions: INSTITUTE OF COMMUNICATION & COMPUTER SYSTEMS, CENTER FOR RESEARCH AND TECHNOLOGY HELLAS, ARISTOTLE UNIVERSITY OF THESSALONIKI, SQUAREDEV, UNIVERSITY OF HELSINKI, UNIVERSITY OF NOVI SAD, VISARIS D.O.O.

The data may also be used by partners working on establishing, testing and maintaining the INCISIVE platform: MAGGIOLI S.P.A., CENTRO REGIONALE INFORMATION ND COMMUNICATION TECHNOLOGY SCRL, BARCELONA SUPERCOMPUTING CENTER – CENTRO NACIONAL DE SUPERCOMPUTACION, EUROPEAN DYNAMICS LUXEMBOURG SA, TELESTO IOT SOLUTIONS LTD.

Details of the INCISIVE project and the beneficiaries can be found at: https://incisive-project.eu/partners/

Furthermore, the data will be made available to other organizations or individual researchers who applied and are approved for access and data use through the INCISIVE platform, in accordance with our data access process. To obtain more information about the list of authorized organizations, please contact us.

The use of your data will be tracked using blockchain technology recording all INCISIVE data transactions, thus ensuring transparency and traceability.

You can share your data through the INCISIVE platform in two ways:

1. Set up a dedicated local data node (what we call a “Federated Node”) at your own premises or any other physical or virtual location of your choice.
2. Use the Central Data Storage facility of the INCISIVE platform.

If you choose to set up your own Federated data Node (solution 1), INCISIVE will provide you with guidelines and technical support for acquiring and installing dedicated hardware (or infrastructure) to operate as an INCISIVE Node. Specifically, you will be guided (or instructed) to acquire and set up infrastructure (i.e. a powerful computer, server, or virtual machine) that will store the data to be shared with the INCISIVE platform. You will also be supported to connect this infrastructure to the INCISIVE platform and act as a Federated Node in the system’s architecture. The node will then be used to facilitate federated data sharing, train AI models and facilitate other data reuse cases, mainly for research purposes. You will receive full technical support from INCISIVE in setting up your Federated Node.

If you are not able to obtain or host a Federated Node within your organization’s infrastructure you can still share data by opting for solution 2 mentioned above, i.e., by utilizing the Central Data Storage facility of INCISIVE (Central Data Node). The Central Node is a GDPR-compliant Central Data storage established and managed by the INCISIVE project. In this case, you will prepare the data you want to share (e.g. de-identify the data, annotate it, and other action described under the data preparation section) and then upload it, through a secure connection to the INCISIVE Central Data Node. You will receive full technical support from INCISIVE for using the Central Node.

In both cases, your data will be harmonized in a Common Data Model to enable its sharing in an interoperable manner and allow AI development. This step is the basis for respecting the FAIR principles (Findability, Accessibility, Interoperability and Reusability) in the INCISIVE platform. The INCISIVE Common Data Model builds on open standards such as DICOM for images, SNOMED CT and LOINC for the non-imaging data semantics. HL7 FHIR is used to enable structural interoperability of non-imaging data. When this procedure is finalised, the data are indexed within the INCISIVE Central Data Infrastructure and specific queries can be performed on them by authorized users.

Please click here for the INCISIVE Node Procurement and Installation Guidelines.

Yes, we offer MedDiSC a data preparation tool for de-identification, annotation and curation of your data that you can use free of charge.
MedDiSC is a web-based application that can be used to de-identify pixel data and attributes of DICOM files. Furthermore, the tool can be used for image segmentation using a graphical user interface. The resulting DICOM files are curated.
MedDiSC has the following features:

• Privacy oriented (All the processing is done locally)
• Easy to use (through a web user interface)
• Standard installation procedure (installed through pip as a Python package)

Additional features include:

• Duplication removal using SHA-256 on the file names
• Allows de-identification of nested DICOM attributes
• Exports segmentation masks in NIfTI files
• Utilizes deep learning models for pixel de-identification and segmentation

Visit https://github.com/valab-certh/meddisc for installation instructions.

Moreover we offer the DIQCT (Data Integration Quality Check Tool) for quality checking of the data under Software Licensing agreement.

DIQCT is a web-based application that can be used to check the data in terms of validity, integrity, consistency, completeness and proper de-identification. The tool produces reports with the errors identified in each quality aspect for clinical and imaging data. The user has to correct the errors and then proceed to the data provision.

For more information on the tool’s components, installation, use and License Agreement you can visit the following link: https://github.com/bioasysauth/quality_tool_platform