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Independent Validation for Medical Imaging AI

An Open Standard for Medical Imaging Dataset Documentation and Provenance

Princeton Medical Systems authored VIDS — an open standard for verifying medical imaging dataset documentation. Independent validation. Signed dataset documentation reports. Designed to support regulatory documentation and procurement review.

Acceptance decisions depend on criteria. PMS authored VIDS, the open Verified Imaging Dataset Standard those criteria can be based on. Buyers, regulators, and procurement teams can use VIDS validation to inform acceptance decisions.

Independent Validation

Datasets validated against VIDS, the open Verified Imaging Dataset Standard. Dataset Documentation Reports issued by an entity with no commercial interest in the dataset itself.

Documentation for Review

Validation Reports designed to support regulatory documentation and procurement review workflows.

Documented Provenance

Every annotation traceable to the credentialed radiologist who created it. Every transformation logged. Every dataset version uniquely identifiable.

Open and Auditable

VIDS is published under CC BY 4.0. The reference validator is open-source on PyPI. Buyers can verify our methodology independently, before they trust our datasets.

Why This Matters

When VIDS is run against widely-used public datasets, results are sobering: BraTS scores 39%, MSD 30%, LIDC-IDRI 27%, CheXpert 20%. These are reference datasets. If they score this low, the question for any buyer is what's in the private vendor delivery they're about to accept.

Defects discovered after acquisition cost more to fix than defects caught before purchase. The cost is paid in rework, in regulatory delays, and in the procurement disputes that follow.

PMS Imaging Standard™

PMS Imaging Standard™ is our commercial implementation of VIDS, the open Verified Imaging Dataset Standard our team authored. Every dataset we deliver is validated against the standard, with the spec, validator, and reference dataset all publicly available so buyers can verify our methodology independently.

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Ingest DICOM Data Validate 21 Rules Radiologist Sign-off Export ML-Ready

Three Ways We Work With You

Validation services for buyers ready to evaluate a dataset they're acquiring. Reference datasets for teams building medical imaging AI. A talent pipeline training the next generation of engineers.

Compliance Evaluation

Independent validation of medical imaging datasets against VIDS. We assess dataset structure, annotation provenance, quality documentation, and ML readiness, then issue a signed Dataset Documentation Report designed to support regulatory and procurement review.

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Reference Datasets

Lung CT and chest X-ray datasets with structured annotations from credentialed radiologists, validated against VIDS, with full provenance documentation. Pre-validated, ML-ready, and licensed for commercial AI development.

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Talent Pipeline

Training the next generation of medical imaging AI engineers through structured courses and university partnerships.

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Built for Your Team

Whether you're in pharma, medtech, research, or clinical operations — we have the data infrastructure you need.

Medtech / Device Companies

Building AI-powered diagnostic devices requires defensible training data. Our VIDS-validated datasets provide traceable provenance and quality documentation to support your path to market clearance.

AI Research Teams

Stop spending months curating data. Start with traceable datasets — with demographic and provenance documentation where available — compatible with MONAI, nnU-Net, and Hugging Face.

Pharma Companies

Need imaging data for companion diagnostics and drug development. We provide datasets with structured provenance and quality documentation.

Clinical Research Organizations

Multi-site imaging studies demand standardized data handling. Our infrastructure ensures consistency and compliance across every site.

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Radiologist-Validated Annotations
Provenance & Quality Documentation
SJIT University Partnership

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