B-Q MINDED · Project

Faster Brain MRI Scans That Catch Disease Earlier with Quantitative Imaging

healthPrototypeTRL 4Thin data (2/5)

Regular MRI scans show pictures of the brain, but the brightness in those images depends on the machine settings — like taking photos with different cameras where colors look different each time. Quantitative MRI fixes this by measuring actual tissue properties in absolute numbers, so doctors can compare scans reliably and spot tiny changes that signal early brain disease. The problem? These advanced scans take too long, making patients uncomfortable and hospitals less productive. B-Q MINDED developed smarter software to process these scans much faster by combining multiple processing steps into one, working with 2 MRI machine makers and 3 software companies to make it practical.

By the numbers

consortium partners across disciplines

countries represented (BE, DE, NL, SE, UK)

SMEs involved including MRI software companies

MRI scanner vendors in the consortium

MRI-software SMEs contributing to development

36%

industry partner ratio in consortium

total project deliverables produced

The business problem

What needed solving

Quantitative MRI can detect early signs of brain diseases that regular MRI misses, but current Q-MRI scans take too long to be practical in hospitals. This means patients endure longer sessions, hospitals process fewer scans per day, and a powerful diagnostic tool remains stuck in research labs instead of helping doctors catch neurodegenerative diseases early.

The solution

What was built

The project built advanced Q-MRI simulation tools on the JEMRIS platform, including in silico tissue models for MR relaxometry and diffusion MRI. These tools enable faster method development and biological interpretation of brain scans, replacing the conventional multi-step processing pipeline with an integrated single-step estimation approach.

Audience

Who needs this

MRI scanner manufacturers (Siemens, Philips, GE) looking to add quantitative imaging featuresMedical imaging software companies developing MRI post-processing productsHospital radiology departments wanting faster brain MRI protocolsNeurology clinics focused on early detection of Alzheimer's and other degenerative diseasesPharmaceutical companies running clinical trials that need reliable brain imaging biomarkers

Business applications

Who can put this to work

Medical imaging equipment

enterprise

Target: MRI scanner manufacturers and MRI software vendors

If you are an MRI equipment manufacturer dealing with hospitals demanding faster scan protocols without sacrificing diagnostic quality — this project developed integrated single-step parameter estimation software that accelerates quantitative MRI processing. The consortium included 2 MRI vendors and 3 MRI-software SMEs who co-developed these tools, meaning the results are designed for real scanner integration.

Hospital radiology departments

enterprise

Target: Large hospitals and radiology clinic chains

If you are a hospital radiology department struggling with long MRI scan times that limit patient throughput and cause discomfort — this project built post-processing methods that speed up quantitative brain MRI. Faster scans mean more patients per day and earlier detection of neurodegenerative diseases, potentially reducing costly late-stage treatments.

Medical imaging software

SME

Target: MRI post-processing and AI diagnostics software companies

If you are an MRI software company looking to add quantitative imaging capabilities to your product — this project created simulation platforms like JEMRIS for advanced Q-MRI and developed methods to replace rigid multi-step processing pipelines. With 5 SMEs in the consortium, the tools were built with commercial software integration in mind.

Frequently asked

Quick answers

What would it cost to license or implement this technology?

The project was a training network (MSCA-ITN-ETN), so IP is distributed across 14 consortium partners including 5 SMEs and 2 MRI vendors. Licensing terms would need to be negotiated with individual partners. Based on available project data, no specific pricing or licensing model is published.

Can this work at industrial scale on existing MRI machines?

The project specifically aimed to make quantitative MRI practical for clinical use by solving the scan time problem. With 2 MRI vendors directly in the consortium, the methods were developed with real scanner compatibility in mind. However, widespread clinical deployment would still require regulatory approval and scanner-specific integration.

What is the IP situation and how can we access it?

IP is likely shared across the 14-partner consortium spanning 5 countries (BE, DE, NL, SE, UK). The 5 industry partners including MRI vendors and software SMEs likely hold commercial rights to specific tools. Contact the coordinator at Universiteit Antwerpen for IP access details.

Is there regulatory approval for clinical use?

Based on available project data, the tools are at the research and development stage. Clinical deployment of quantitative MRI methods would require medical device certification (e.g., CE marking for software as a medical device). The simulation tools like JEMRIS may be usable for research without regulatory constraints.

What was actually built and delivered?

The project produced 7 deliverables including advanced Q-MRI simulation tools built on the JEMRIS platform. These include in silico tissue models for MR relaxometry and diffusion MRI, enabling method development and biological interpretation without needing actual patients for testing.

How long before this could be used in a hospital?

The project ran from 2018 to 2022 and is now closed. The post-processing methods and simulation tools exist, but transitioning from research to clinical product typically requires further validation, regulatory steps, and commercial packaging. Based on available project data, no timeline for clinical deployment is specified.

Consortium

Who built it

The B-Q MINDED consortium is well-balanced for translating research toward industry with 14 partners across 5 European countries. The 36% industry ratio is notably strong for a training network, with 5 industry partners including 2 major MRI scanner manufacturers and 3 MRI-software SMEs working alongside 6 universities and 3 research organizations. This mix means the post-processing methods were developed with direct input from the companies that build and sell MRI equipment and software — a good sign for eventual commercial viability. The coordinator, Universiteit Antwerpen in Belgium, anchors the academic side while industry partners ensure practical relevance.

UNIVERSITEIT ANTWERPENCoordinator · BE
LINKOPINGS UNIVERSITETpartner · SE
ICOMETRIX NVparticipant · BE
UNIVERSITAETSKLINIKUM AACHENpartner · DE
THE UNIVERSITY OF SHEFFIELDparticipant · UK
FORSCHUNGSZENTRUM JULICH GMBHparticipant · DE
QUANTIB BVparticipant · NL
STICHTING NETHERLANDS ESCIENCE CENTERpartner · NL
UNIVERSITY OF LEEDSparticipant · UK
UNIVERSITAIR ZIEKENHUIS ANTWERPENparticipant · BE
ERASMUS UNIVERSITAIR MEDISCH CENTRUM ROTTERDAMparticipant · NL

How to reach the team

Universiteit Antwerpen (Belgium) — use SciTransfer's coordinator lookup service to find the right contact person

Order a report on this consortium See UNIVERSITEIT ANTWERPEN profile →

Next steps

Talk to the team behind this work.

Want to explore how faster quantitative MRI processing could fit your product roadmap or clinical workflow? SciTransfer can connect you directly with the research team and help navigate IP access across the 14-partner consortium.

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