Updated on 28 October 2026
volBrain: validated AI pipelines for MRI imaging biomarkers in neurology
volBrain.net research team at volBrain research
Valencia, Spain
About
WHO WE ARE
volBrain is an academic, free-access cloud platform for medical image analysis created by the Image Processing and AI group at ITACA (Universitat Politècnica de València), with CNRS / University of Bordeaux (LaBRI). Since 2015 it has made research-grade MRI analysis available to clinicians and researchers who lack computing resources or technical expertise: upload an image, get a standardized quantitative report (PDF, CSV and NIfTI segmentations) in about 20 minutes. The volbrain.net platform has processed more than 800,000 cases for over 1,600 users in more than 4,600 institutions worldwide, and more than 800 publications have used our tools. It is funded by Spanish (MINECO/MICIU) and French (ANR: DeepvolBrain, TRAIL) national programmes.
WHAT WE OFFER (Partner seeks Consortium/Coordinator)
We offer expertise as a Partner or work package leader in medical image analysis and AI-based imaging biomarkers, with ready-to-use, validated pipelines:
-
vol2Brain / volBrain: whole-brain parcellation (>130 structures), tissues, cortical thickness, white matter lesions.
-
AssemblyNet (+ AD and AD-FTD versions): deep learning parcellation (> 130 strctures) and prediction/differential diagnosis of Alzheimer’s disease and frontotemporal dementia.
-
lesionBrain / DeepLesionBrain: white matter lesion segmentation on T1w and FLAIR, with disconnectome maps (e.g. multiple sclerosis).
-
cognitiveTree and motorTree: decision support for differential diagnosis of cognitive and motor disorders.
-
petBrain: amyloid, tau and neurodegeneration status from MRI and PET.
-
HIPS, DeepThalamus, DeepCERES, pBrain: hippocampal subfields, thalamic nuclei, cerebellar lobules, deep and subthalamic nuclei.
-
BrainStructureAges: brain age and age per structure as a biomarker of ageing and disease.
VALUE PROPOSITION AND COMPETITIVE ADVANTAGE
Our pipelines turn raw MRI into reproducible volumetric and diagnostic biomarkers without local infrastructure, which lowers the barrier for hospitals and trials. Compared with typical academic tools, they are already deployed as a service, validated in peer-reviewed publications, robust to multi-centre and multi-scanner data, and fast. Our large user community provides continuous real-world feedback and visibility for any project we join.
MATURITY
Our core pipelines (volBrain, vol2Brain, AssemblyNet, lesionBrain) are mature and operate as a public service used worldwide. Newer diagnostic tools (cognitiveTree, motorTree, petBrain, AssemblyNet-AD/FTD) are validated on research cohorts and ready for prospective clinical validation.
WHAT WE CAN CONTRIBUTE TO A CLUSTER 1 HEALTH PROPOSAL
-
Leadership of an imaging / AI analysis work package.
-
Adaptation and validation of our pipelines on project cohorts (neurological, neurodegenerative, neuropsychiatric, neuro-oncological), and extension to new modalities and organs.
-
Imaging biomarkers for early diagnosis, patient stratification, progression and treatment-response monitoring in clinical studies and trials.
-
Scalable cloud processing with harmonized outputs ready for statistical analysis, privacy-preserving deployment in collaboration with clinical partners.
-
Methodological research: domain adaptation and harmonization across sites, uncertainty estimation, explainable AI, normative and brain-age models, learning with limited annotations.
TEAM
Led by Prof. José V. Manjón (UPV) and Dr. Pierrick Coupé (CNRS, Univ. Bordeaux), with a long-standing record in image processing, deep learning and neuroimaging, and close ties with clinical groups.
WHO WE ARE LOOKING FOR
-
Coordinators building 2027 consortia that need an imaging analysis partner.
-
Hospitals and clinical research centres with imaging cohorts who want to validate biomarkers in real clinical settings.
-
Pharma, biotech and medtech companies (including SMEs) running neuroscience trials or seeking to integrate imaging biomarkers in products.
-
AI, radiomics, genomics and digital health groups for multimodal approaches.
Contact: team@volbrain.net | www.volbrain.net
Topic
- Destination 3: HORIZON-HLTH-2027-01-DISEASE-10: Prevention and management of chronic non-communicable diseases in children and young people (GACD)
- Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
- Destination 3: HORIZON-HLTH-2027-02-DISEASE-14-two-stage: Clinical trials for advancing innovative interventions for neurodegenerative
- Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
- Destination 5: HORIZON-HLTH-2027-03-TOOL-08: Towards the next generation of frontier Artificial Intelligence models for healthcare
- Destination 5: HORIZON-HLTH-2027-03-TOOL-04: Virtual Human Twins (VHTs) for integrated clinical decision support in prevention and diagnosis
Type
- Partner seeks Consortium/Coordinator
Organisation
Similar opportunities
Project cooperation
AI partner for multimodal predictive biomarkers (HORIZON-HLTH-2027-02-TOOL-01)
- Partner seeks Consortium/Coordinator
- Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Shadi Albarqouni
Professor of Computational Medical Imaging Research at Albarqouni Lab. @ University Hospital Bonn | University of Bonn
Bonn, Germany
Project cooperation
- Destination 3: HORIZON-HLTH-2027-02-DISEASE-01-two-stage: Innovative healthcare interventions for non-communicable diseases
- Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
Indre Ceponiene
Professor of Cardiology, Vice-Rector for Studies at Lithuanian University of Health Sciences
Kaunas, Lithuania
Project cooperation
Research-use IAS image and genomic data integration partner for predictive biomarker consortia
- Partner seeks Consortium/Coordinator
- Destination 5: HORIZON-HLTH-2027-02-TOOL-01-two-stage: Development of predictive biomarkers of disease progression and treatment response by using AI methodologies for chronic non-communicable diseases
daisuke kubota
Founder and CEO at Life Analytics Co., Ltd.
Yokohama, Japan