RWID · For Foundation Model Developers and Medical Devices Companies

Large-scale real-world imaging data for foundation models, from pipeline to production to FDA

See what’s available for your modality
Talk to our team
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Millions of centralized, de-identified imaging studies across many vendors and sites, ready for training, fine-tuning, and validation.
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50+
FDA-cleared devices built on Segmed data network
HIPAA
Safe Harbor + Expert Determination methods
2,800
Healthcare partner sites

Challenge

Pre-training is a data problem. So is everything after it.

Generalist imaging models require diverse, large-scale real-world data.

The breadth of training data determines how well models generalize across sites, vendors, populations, and clinical scenarios. From pre-training through validation, regulatory clearance, and deployment.

‍Every one of these stages comes back to the same fundamental question: has the model been exposed to enough of the real world? Limited data diversity constrains performance at the pre-training stage and continues to surface during generalizability evaluation.

Segmed is purpose-built around imaging, with a centralized, unified, de-identified corpus designed to support the full model lifecycle, from pre-training and fine-tuning to validation across diverse clinical scenarios.

What You Get

One network, the whole model lifecycle
Our Foundation Model datasets are large-scale, multi-vendor imaging collections, designed to enable the full model lifecycle: from first pre-training run to FDA clearance.

Modalities

Know what you’re training on
Foundation model teams need comprehensive imaging coverage across anatomy, modalities, and clinical settings, not a single headline number. A live snapshot of the network, by modality:

Use Cases

How can Segmed accelerate your development?
Segmed supports four persona-aligned use cases across the product development lifecycle.
Request datasets
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Foundation Model Dev /
ML lead (Big Tech & Frontier Labs)

Person holding a medical scan while using a laptop showing another scan image on its screen.

Scale and diversity to train generalist medical imaging models: Access broad, multi-vendor, multi-site imaging datasets spanning anatomies and modalities, centralized in one source so your models learn from the full distribution, not fragmented datasets.

AI / ML lead (SaMD & Medical Device Companies)

Person holding tablet with digital AI chip and circuit board interface overlay.

Improve model performance and generalizability before deployment: Close the gap between controlled development environments and real-world performance with targeted diversity for training, fine-tuning, and validation on clinically representative data.

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Regulatory and
Clinical Validation

Evidence that models generalize safely across populations and sites: Build FDA-ready evidence with independent, multi-site validation cohorts featuring clinical provenance, demographic diversity, and end-to-end data lineage.

Founder / VP Product

Three people working at a table with a laptop, charts, and notes in a notebook and sticky notes.

Reduce execution risk across the entire product lifecycle: Accelerate your roadmap with a single data partner supporting foundation model development, product validation, regulatory submissions, and post-market monitoring.

Why Segmed

Built imaging-first.
Across the whole lifecycle.
A model only generalizes on the breadth it was built on. Segmed is the centralized, imaging-first data partner that gives you that breadth and the documentation to defend it, from the first pre-training run to the FDA.

Imaging at Scale

Segmed

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150M+ studies, with 10M+ deliverable within days

Others

Limited or none

Imaging + EHR linkage

Segmed

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3.5M patients linked

Others

Partial or absent

Built imaging-first

Privacy-preserving

Segmed

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Yes

Segmed

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Yes

Others

None

Others

Varies

Outcomes

Proven where it counts. 50+ FDA-cleared medical devices have been built on Segmed data network.
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Proven, pipeline to FDA

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Powering large-scale pre-training, fine-tuning and FDA-grade validation for leading medical-imaging AI developers across CT, MRI, X-ray, mammography, PET and ultrasound.

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Published research

Peer-reviewed work on applications of real-world imaging data for foundational models use cases.

Access timeline

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Data in days, not months. Compliance infrastructure (de-identification, provenance documentation) managed on the platform.

Dataset Request

See what’s available for your model
Tell us the modality, body part, and population you’re training or validating on. We’ll send a modality breakdown and volume.
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Frequented Asked Questions - F.A.Q.

Can Segmed's real-world imaging data support large-scale pre-training?

Yes, millions of studies, full anatomy across modalities, vendors, and sites: the non-curated breadth generalist models need. Ask for the modality breakdown.

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Can the same network handle validation later?

That’s the point: one centralized network across the full lifecycle: pre-train, fine-tune, validate, clear, and monitor, without re-sourcing at each stage.

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Why centralized over federated?

You can pool and train/validate across the whole corpus consistently; federated networks struggle when data must leave its source. Segmed stays privacy-preserving via automated de-identification.

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How is the data de-identified?

Segmed has obtained a global Expert Determination certification covering its data assets, including structured clinical data, medical imaging pixels, and radiology text. This certification is applied at the platform level and not on a per-dataset basis. For all data deliveries, Segmed applies the HIPAA Safe Harbor de-identification method to remove PHI identifiers prior to delivery.

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How fast can I access data?

Within days, not months.

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