Bigpicture

What Bigpicture does

Bigpicture is a European public-private partnership research consortium launched in March 2021 and coordinated by Radboudumc (Nijmegen, Netherlands) under EU Innovative Medicines Initiative 2 Joint Undertaking grant agreement No. 945358, with co-funding from Horizon 2020 and EFPIA member companies. Its mission is to accelerate AI development in pathology by building Europe's largest repository of digital whole-slide images (WSIs) — targeting 3 million annotated slides — accessible to academic researchers, hospital pathologists, pharmaceutical companies, and AI developers under a GDPR-compliant Data Sharing Agreement signed by 44 partner institutions across academia, healthcare, pharma (Bayer, Novartis, Janssen), and technology providers.

The platform is built on Cytomine, an open-source web-based viewer and annotation system, and integrates a suite of proprietary AI tools developed within the consortium: TANGO for objective stain-quality assessment, an Artifact Segmentation Model (DeepLab V3+/EfficientNet-B2) for automated QC, a Whole-Slide Image Registration tool (DeeperHistReg, winner of the ACROBAT challenge at MICCAI 2023), Content-Based Image Retrieval for visual-similarity search, StreamingCLAM for scalable weakly-supervised learning, plus supporting infrastructure (Data Transporter, SlideTap, DICOM Formatting Tools) that cut WSI conversion time from ~4 minutes to ~10 seconds per slide. Notable data contributors include Novartis (5,000+ slides uploaded, 400,000-slide target) and Helsinki University Hospital (8,000+ slides scanned).

Bigpicture does not operate as a commercial entity: it has no revenue, no pricing model, and no commercial customers. Access to the platform is governed by consortium membership and a Data Sharing Agreement. The project is currently in its final IMI funding phase, with Work Package 6 (WP6, launched 2024) explicitly chartered to design post-grant sustainability, governance, and regulatory frameworks — and consortium partners unanimously supported a project extension at the January 2026 Berlin Annual Meeting, signaling institutional commitment to continuity as a permanent European pathology-AI infrastructure.

Name

Bigpicture

Legal name

Bigpicture

Website

https://bigpicture.eu

Company type

Private

Founded year

2021

Operating status

Operating

Headcount range

1–10 employees

Short description

Bigpicture is a publicly funded EU research consortium (IMI 2 grant 945358) building Europe's largest digital pathology repository — targeting 3 million annotated whole-slide images — and an integrated AI tool suite on Cytomine, serving academic researchers, hospital pathologists, pharmaceutical companies, and AI developers.

Ownership category

akta.pro rank

Product category

Digital Pathology Platform

NAICS

Software Publishers (51321)

SIC

Services-Prepackaged Software (7372)

akta.pro primary industry

Medical Imaging AI (HDAAAEAH)

akta.pro secondary industries

Vendor Neutral Archive (VNA) & Enterprise Imaging Repositories (HLACALAC), Radiology AI, CAD & Advanced Visualization Software (HLAHABAJ), Molecular Pathology & Tissue Biomarkers (IHC/ISH, digital pathology-linked markers) (HLAAAMAI), Healthcare Terminology, Ontology & Code Set Management (SNOMED/LOINC/ICD/RxNorm) (HLACAIAF)

Keywords

• Digital pathology platform
• Whole-slide imaging
• Pathology AI tools
• Computational pathology
• Medical image repository

GTM type

B2B

Offering type

Software

Cost components

Technology or R&D, Personnel, Operations

Distribution channels3 records

Marketing channels7 records

Core offering

Bigpicture is a public-private partnership research consortium that creates and operates a large-scale digital pathology repository and AI platform for uploading, storing, annotating, sharing, and analyzing digitized whole-slide pathology images (WSIs) across Europe. The platform is built on the Cytomine open-source web platform and integrates AI tools for quality control, image retrieval, registration, and annotation. It serves academic researchers, clinical pathologists, pharmaceutical companies, and AI developers as a shared, GDPR-compliant research infrastructure rather than a commercial product.

Product overview

Bigpicture is a public-private partnership (EU IMI-funded) that functions as a large-scale digital pathology research infrastructure. At its core is the Cytomine open-source web platform, which serves as the primary interface for uploading, viewing, annotating, and analyzing whole-slide pathology images (WSIs). The platform integrates a suite of AI-powered tools developed within the consortium: TANGO for stain quality assessment, the Artifact Segmentation Model for automated slide QC, a WSI Registration Tool for aligning multi-stain images, Content-Based Image Retrieval (CBIR) for visual similarity search, and StreamingCLAM for scalable weakly-supervised AI training. Supporting infrastructure includes the Data Transporter (secure data upload tool), SlideTap (metadata conversion), and DICOM Formatting Tools (format standardization). A dedicated Work Package 6 (WP6) addresses sustainability, regulatory frameworks, and governance. The platform is designed for use by academic researchers, hospital pathologists, pharmaceutical companies, and AI developers across Europe.

Differentiator

Problem solved

Functional benefit

Brands

• Cytomine: Open-source web-based software platform for uploading, annotating, sharing, and analyzing pathology imaging data integrated into the Bigpicture platform.
• Data Sharing Agreement (DSA)
• TANGO
• Data Transporter
• SlideTap
• StreamingCLAM

Products and services

• Bigpicture Digital Pathology Platform A large-scale digital pathology repository and AI platform providing central infrastructure for uploading, storing, annotating, exploring, and analyzing digitized whole-slide images (WSIs) across Europe. Built on the Cytomine open-source web platform, it integrates AI tools for quality control, image retrieval, registration, and annotation. Designed to serve academic researchers, pathologists, pharmaceutical companies, and AI developers.
• Cytomine Open-source web-based viewer and annotation platform integrated into Bigpicture for uploading, sharing, exploring, and collaboratively annotating whole-slide pathology images in-browser. Supports multi-user collaboration, AI-assisted annotation, and the deployment of AI models (App Engine) directly within the viewer. Scaled to handle millions of slides with authentication and authorization.
• TANGO (Tissue-stain ANalysis and Grading Objective tool) A biopolymer film-based standardization tool for objectively assessing stain consistency across labs. Used within Bigpicture to evaluate stain variability across contributing sites and improve AI training data quality by ensuring uniform, high-quality staining across the repository. Developed by Leeds Teaching Hospitals NHS Trust.
• Artifact Segmentation Model A deep learning semantic segmentation model (DeepLab V3+ with EfficientNet-B2 encoder) that automatically identifies and classifies six artifact types in whole-slide images: tissue folds, dust particles, out-of-focus regions, ink marks, pen markers, and air bubbles. Provides quantitative quality scores and visual segmentation masks for each slide. Trained on 121 annotated slides across 13 tissue types, 9 stain types, and 7 scanner models; evaluated on 500+ cases.
• Whole-Slide Image (WSI) Registration Tool A registration algorithm originally from radiology/radiotherapy, adapted for histology to align multiple WSIs of the same tissue sample under different stains (e.g., H&E and IHC) into a unified spatial reference. Uses pre-alignment, parametric registration, and non-parametric pixel-level registration. Available as a Python package and integrated into Cytomine, developed by Fraunhofer MEVIS.
• Content-Based Image Retrieval (CBIR) A search tool enabling users to query the Bigpicture repository by visual similarity rather than keywords. Allows researchers to find rare cases, build training cohorts, and explore data by image content across the platform's datasets.
• StreamingCLAM An end-to-end weakly-supervised deep learning framework that processes WSIs as streams, maintaining global tissue context while learning from slide-level labels. Designed for scalable, collaborative AI model training without requiring patch-by-patch loading of entire images.
• Data Transporter A secure software tool operating within contributors' firewalls that enables non-clinical data contributors to prepare, validate, encode sensitive information, encrypt, and upload pathology datasets to the Bigpicture platform while maintaining full control over data submission. Developed by Deciphex.
• SlideTap A metadata conversion tool that transforms data from diverse local IT systems, Excel files, or manual entry into Bigpicture's required format, bridging the gap between local data structures and the platform's metadata standards.
• DICOM Formatting Tools Python-based DICOM reader and writer tools developed by WP4 for converting whole-slide images from proprietary formats (Aperio, Hamamatsu NDPI, Philips TIFF, Zeiss CZI, Leica SCN, Ventana BIF, Olympus VSI, OME-TIFF, Mirax, Sakura SVSlide, Trestle TIF) into the DICOM standard. Includes fast conversion (from approximately 4 minutes per slide to approximately 10 seconds) and a graphical user interface. Developed by Sectra.

Quantifiable outcome

• 3 million whole slide images targeted for repository
• +3 more outcomes

Segments4 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

AI capability5 records

Feature10 records

Partnerships

19 partnerships are on record, tiered core and supporting.

• BayercoreStrategic or Co-development PartnerEFPIA partner contributing non-clinical datasets, metadata development, and AI activities. Hosted 2026 Annual Meeting in Berlin. Key contributor to preclinical pathology and digital workflows.
• NovartiscoreStrategic or Co-development PartnerEFPIA Leader of Work Package 1, with Head of Digital and Computational Pathology (Julie Boisclair) leading industry coordination. Has uploaded over 5,000 slides with target of 400,000 slides.
• University Medical Centre Utrecht (UMCU)coreStrategic or Co-development PartnerPartner in Work Package 3, responsible for gathering data, harmonizing metadata, and coordinating dataset uploads. Led by Nikolas Stathonikos.
• Helsinki University Hospital (HUS)coreStrategic or Co-development PartnerClinical data contributor managing the lung node in Work Package 3. Successfully completed first real data upload with over 8,000 slides scanned. Leading honest broker mechanism development.
• University of Liège (ULiège)coreTechnology or IntegrationLeads Cytomine open-source platform development and maintenance. Team led by Raphaël Marée rebuilt critical components after Cytomine company bankruptcy, scaling system to millions of slides.
• Uppsala UniversitycoreStrategic or Co-development PartnerHosted 2025 Annual Meeting in Uppsala, Sweden with 137 participants. Contributing to computational pathology and AI research through Bigpicture.
• Janssen (Johnson & Johnson)coreStrategic or Co-development PartnerPharmaceutical partner and sponsor of 2024 Annual Meeting in Liège, Belgium. Represented by Anna-Lena Frisk, WP1 Scientific Director Pathology.
• Medical University ViennacoreStrategic or Co-development PartnerHosted 2023 Annual Meeting (second consortium meeting) in Vienna with 150+ participants. WP3 led by Renate Kain.
• NHS (National Health Service)coreStrategic or Co-development PartnerUK National Health Service partner working on scaling data upload to Bigpicture platform. Mentioned at 2026 Annual Meeting.
• VICT3RcoreStrategic or Co-development PartnerIHI project focused on virtual control groups to reduce animal testing in toxicology research. Collaboration connects VICT3R's structured tabulated data with Bigpicture's image data infrastructure for integrated analysis.
• Radboudumc (Computational Pathology Group)coreStrategic or Co-development PartnerLed by Jeroen van der Laak (Bigpicture Coordinator) and Geert Litjens. Core academic partner developing AI tools including StreamingCLAM and artifact segmentation models. Recipient of Ammodo Science Award 2024.
• Fraunhofer MEVIScoreTechnology or IntegrationDeveloping whole slide image registration algorithm adapted from radiology for histology. Team led by Daniel Budelmann integrating registration tool into Cytomine platform.
• CSC (ELIXIR node)supportingTechnology or IntegrationFinnish IT center and ELIXIR node collaborating on data upload workflows and platform infrastructure.
• BetawerksupportingTechnology or IntegrationWebsite hosting provider based in Heerlen, Netherlands. Listed as responsible body for data processing on the Bigpicture website.
• DeciphexcoreTechnology or IntegrationDeveloping Data Transporter tool for secure data submission. Team includes Caitríona Lyons (WP3 node-coordinator for non-clinical safety) and Pierre Moulin (Chief Scientific Officer).
• SectracoreTechnology or IntegrationSwedish company providing DICOM tooling expertise. Erik O Gabrielsson (Research Engineer) developing conversion tools and user interfaces for WSI format standardization.
• Leeds Teaching Hospitals NHS TrustsupportingStrategic or Co-development PartnerTeam including David Brettle, Hayley Pye, and Catriona Dunn developed TANGO stain assessment tool and presenting on quality assurance in digital pathology.
• HES-SO Valais (MedGIFT Group)supportingTechnology or IntegrationSwiss research group contributing to content-based information retrieval and WSI registration. Marek Wodzinski leads DeeperHistReg library development.
• OwkinsupportingTechnology or IntegrationAI/healthcare company with expertise in federated learning for digital histopathology. Jean Ogier du Terrail presented on challenges and opportunities in federated learning.

Scale indicators8 records

Recent moves6 records

Expansion highlights6 records

Broad incumbents

• Sectra: Established medical imaging IT vendor providing enterprise PACS/VNA and digital pathology modules; provides DICOM tooling expertise to Bigpicture and competes broadly for the same hospital IT budgets.
• Philips Digital Pathology: Broad medical imaging incumbent with a digital pathology portfolio (IntelliSite) addressing hospital pathology workflows and AI integration — a wider portfolio incumbent competing for similar enterprise imaging contracts.
• Roche (Ventana): Incumbent in tissue diagnostics (stains, instruments, digital pathology workflow via Ventana) and the largest pathology staining/imaging provider globally — a broad incumbent with overlapping AI pathology ambitions.

Emerging players

• Aignostics: Berlin-based AI pathology spin-out from Charité building computational pathology models for pharma R&D — emerging European player with strong overlap in AI-for-pathology research and pharma use cases.

Direct peers

• Paige.AI: Digital pathology AI company focused on cancer diagnosis and biomarker discovery — directly comparable product scope (AI on whole slide images for clinical and research pathology) and similar pharma/biopharma partnership model.
• Deciphex: Digital pathology software company developing tools for pathology workflow and AI deployment, including the Data Transporter used by Bigpicture — closely comparable product and a current Bigpicture technology partner.
• PathAI: Commercial AI pathology company building diagnostic and drug-development tools on large annotated pathology datasets — directly comparable in mission (AI for pathology at scale) and target customer base (pharma + academic pathology) even though its model is proprietary rather than consortium-based.
• Ibex Medical Analytics: AI-based cancer diagnostics company deploying deep-learning models on whole slide images for clinical pathology — directly comparable product (AI-powered pathology image analysis) and similar clinical and biopharma positioning.
• Proscia: Digital pathology platform company providing an enterprise cloud platform for pathology image management, AI integration, and analytics — directly comparable platform play serving biopharma and clinical labs.
• Owkin: Federated-learning AI company with deep histopathology expertise and active Bigpicture collaboration; comparable in offering AI on pathology data at multi-institutional scale and serving pharma research workflows.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks6 records

Key highlights6 records

Customer concentration

• LinkedInlinkedin.com/company/bigpicture-project

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Profiles14 records

Funding overview

Funding rounds

Investors

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M&A

Investments

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Frequently asked questions about Bigpicture