If you are a radiology department dealing with growing scan volumes and inconsistent diagnostic accuracy — INCISIVE developed an AI toolbox validated across 8 pilot sites and 2,600 patients that improves sensitivity and specificity of cancer detection. The system covers breast, prostate, colorectal, and lung cancer imaging, and includes explainable AI so radiologists can understand and trust the results.
AI Cancer Imaging Tools That Improve Diagnosis Accuracy Across Four Cancer Types
Imagine if every hospital could tap into the same massive pool of cancer scans to train smarter diagnostic software — but without anyone's private data ever leaving their hospital. That's what INCISIVE built: an AI system that reads breast, prostate, colorectal, and lung cancer images, trained on a petabyte of data from 8 hospitals across 5 countries. Think of it like a second pair of expert eyes for radiologists, one that gets better the more hospitals join, while keeping patient data locked down with blockchain-grade security.
What needed solving
Cancer diagnosis from medical imaging is inconsistent across hospitals, limited by small local datasets, and expensive when relying on high-end scanning methods. Radiologists face growing scan volumes while AI tools remain siloed because patient data cannot be freely shared between institutions. This means promising AI diagnostics never reach their full accuracy potential, and patients in smaller hospitals get lower-quality readings.
What was built
INCISIVE built three main products: (1) an AI toolbox for cancer image analysis covering breast, prostate, colorectal, and lung cancer with explainable AI and automated annotation, (2) a pan-European federated repository of health images enabling secure data sharing without moving patient data, and (3) integrated prototypes validated through pilot studies at 8 sites with 2,600+ patients. All three were delivered as final versions incorporating pilot feedback.
Who needs this
Who can put this to work
If you are a health IT company looking to integrate AI-powered cancer diagnostics into your platform — INCISIVE built a ready-to-integrate AI toolbox with automated annotation and data analytics services. The federated learning architecture means your clients' data stays on-premise while still benefiting from models trained across 5 countries. The system was tested with 28 consortium partners, including 11 industry players.
If you are a health insurer trying to reduce costs from late-stage cancer diagnoses — INCISIVE demonstrated AI models that improve accuracy of lower-cost scanning methods, potentially catching cancers earlier when treatment is cheaper. Validated across 4 cancer types with at least 2,600 patients, the system also predicts tumor spread, evolution, and relapse, helping you plan care pathways more effectively.
Quick answers
What would it cost to deploy this AI system in our hospital or company?
The project does not publish specific licensing or deployment costs. INCISIVE was funded as a Research and Innovation Action, so the technology was developed with public funding. Commercial terms would need to be negotiated with the consortium, led by Maggioli SPA (Italy). The system is designed as modular services (AI Toolbox, Data Analytics, User Services), which may allow flexible pricing.
Can this scale to handle our imaging volume across multiple sites?
Yes — the system was specifically designed for multi-site operation. It was validated across 8 pilot sites in 5 countries (Cyprus, Greece, Italy, Serbia, Spain) using federated learning, meaning the AI trains across sites without moving patient data. The repository was built to handle 1 PB of imaging data from 8 data-providing partners.
What about IP and licensing — who owns this technology?
INCISIVE was developed by a 28-partner consortium led by Maggioli SPA, a large Italian IT company. IP ownership typically follows EU Horizon 2020 grant rules, where each partner owns the results they generate. Licensing arrangements would need to be discussed with the coordinator and relevant partners who developed specific components.
Does this meet healthcare data regulations like GDPR?
The project was explicitly designed for compliance with ethical, legal, and privacy demands. It uses federated learning so patient data never leaves the originating hospital. The pan-European repository includes blockchain-based mechanisms for secure data donation and sharing. Based on available project data, the system addresses GDPR requirements by design.
How long would implementation take?
The project ran from October 2020 to March 2024 and delivered final versions of all major components: the AI Toolbox, the Pan-European Repository, and the integrated prototypes. Pilot validations ran for 1.5 years across 8 sites. Based on available project data, the technology has been validated but would require integration work specific to your environment.
Which cancer types does this actually cover?
INCISIVE validated its AI models across 4 cancer types: breast, prostate, colorectal, and lung cancer. These were tested in dedicated validation studies at 8 pilot sites with at least 2,600 patients participating. The models handle various cancer imaging scans, biological data, and electronic health records.
Is there ongoing support or is this a finished research project?
The project officially closed in March 2024. However, with 28 partners including 11 industry organizations and 7 SMEs, several consortium members are likely pursuing commercial exploitation. The final deliverables include a stand-alone pan-European repository system and production-ready AI services. Contact the coordinator for post-project support options.
Who built it
The INCISIVE consortium is unusually large at 28 partners across 9 countries, with a strong industry presence: 11 industry partners (39% of the consortium) including 7 SMEs. This mix signals serious commercial intent beyond pure research. The coordinator, Maggioli SPA, is a well-established Italian IT company (not an SME), which provides business credibility and potential for post-project commercialization. With 8 universities and 6 research organizations providing the scientific backbone, and industry partners handling technology development and market access, this consortium is well-positioned to move results toward the market. The geographic spread across Southern and Eastern Europe (with UK and Belgium) covers key healthcare markets.
- MAGGIOLI SPACoordinator · IT
- UNIVERSITA DEGLI STUDI DI ROMA TOR VERGATAparticipant · IT
- ADAPT IT AEparticipant · EL
- TIMELEXparticipant · BE
- PAGKYPRIOS SYNDESMOS KARKINOPATHON KAI FILON 1986participant · CY
- HELSINGIN YLIOPISTOparticipant · FI
- TECHNOLOGIKO PANEPISTIMIO KYPROUparticipant · CY
- ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXISparticipant · EL
- EUROPEAN DYNAMICS ADVANCED INFORMATION TECHNOLOGY AND TELECOMMUNICATION SYSTEMS SAthirdparty · EL
- THRIDIUM LIMITEDparticipant · UK
- ELLINIKI ANTIKARKINIKI ETAIREIAparticipant · EL
- ETHNIKO KAI KAPODISTRIAKO PANEPISTIMIO ATHINONparticipant · EL
- ARISTOTELIO PANEPISTIMIO THESSALONIKISparticipant · EL
- CENTRO REGIONALE INFORMATION E COMMUNICATION TECHNOLOGY SCARLparticipant · IT
- EUROPEAN DYNAMICS LUXEMBOURG SAparticipant · LU
- UNIVERSITA DEGLI STUDI DI NAPOLI FEDERICO IIparticipant · IT
- SQUAREDEVparticipant · BE
- WHITE RESEARCH SRLparticipant · BE
- MEDTRONIC IBERICA SAparticipant · ES
- FUNDACIO DE RECERCA CLINIC BARCELONA-INSTITUT D INVESTIGACIONS BIOMEDIQUES AUGUST PI I SUNYERparticipant · ES
- KINGSTON UNIVERSITY HIGHER EDUCATION CORPORATIONparticipant · UK
- HOSPITAL CLINIC DE BARCELONAthirdparty · ES
- UNIVERZITET U NOVOM SADUparticipant · RS
- FUNDACIO TICSALUT I SOCIALparticipant · ES
- EREVNITIKO PANEPISTIMIAKO INSTITOUTO SYSTIMATON EPIKOINONION KAI YPOLOGISTONparticipant · EL
- BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACIONparticipant · ES
Maggioli SPA (Italy) — use SciTransfer coordinator lookup to find the project contact
Talk to the team behind this work.
Want to explore how INCISIVE's AI cancer imaging tools could work for your organization? SciTransfer can connect you directly with the right people in the consortium. Contact us for a tailored introduction.