About Princeton Medical Systems

Building the Future of Medical Imaging Data Infrastructure

The medical AI industry's biggest bottleneck isn't models — it's data quality, traceability, and compliance. We exist to solve that.

Our Story

From a Gap in the Market to a Mission

Founded in March 2024, Princeton Medical Systems is headquartered in Chennai, India. We specialize in building the data infrastructure layer for medical imaging AI.

The catalyst was clear: as clinical AI adoption accelerates, the gap between model sophistication and data quality keeps widening. Models are getting better — but the datasets they train on remain inconsistent, poorly documented, and often non-compliant with regulatory requirements.

We set out to build the missing layer — the infrastructure that ensures every medical imaging dataset is clinically validated, fully traceable, bias-aware, and compliance-ready before it ever reaches a model.

Our Mission

To build the definitive data infrastructure for medical imaging AI — making every dataset clinically validated, fully traceable, and compliance-ready.

Our Vision

A future where every clinical AI model is trained on verified, bias-aware, regulatory-grade imaging data.

Our Journey

Company Timeline

March 2024

Founded

Princeton Medical Systems established with a mission to solve medical imaging data quality.

Mid 2024

First DICOM Tools Launched

Released initial suite of DICOM conversion and de-identification tools for developers.

Late 2024

PMS Imaging Standard Development

Began development of our proprietary dataset validation and certification framework.

Early 2025

Talent Pipeline Established

Published Udemy courses and established structured training programs for medical imaging AI engineers.

January 2026

SJIT University Partnership

Signed MOU with SJIT University to advance medical imaging AI education and research.

2025

Dataset Curation Begins

Initiated radiologist-annotated dataset curation for lung CT and chest X-ray imaging.

2026

Full Platform Expansion

Expanding the platform with new datasets, tools, and enterprise partnerships.

Leadership Team

Dr. Joan S. Muthu, Ph.D.

Co-Founder & Chief Technology Officer

Dr. Joan S. Muthu brings over 14 years of experience in DICOM engineering, medical image interoperability, and AI/ML for medical imaging. She holds a Ph.D. in Computer Science and Engineering, with doctoral research in DICOM file security that led to a granted Indian patent and a Gold Medal for Best Research Paper. Joan has published six peer-reviewed papers in SCI- and Scopus-indexed journals and serves as a peer reviewer for Springer Nature.

At Princeton Medical Systems, Joan leads the development of end-to-end medical imaging data pipelines — from cross-format image conversion and interoperability to large-scale dataset curation and the company's proprietary dataset verification framework — ensuring every dataset is spatially accurate, metadata-complete, and fully traceable.

John Shalen R

Co-Founder & Chief Operating Officer

John Shalen R brings a distinctive combination of clinical data standards expertise, statistical programming, and hands-on operational leadership to the company's mission. He has direct experience in regulatory-aligned data workflows, having developed and validated clinical trial datasets to CDISC standards (SDTM & ADaM) using R and SAS. John previously built a company's team and operational infrastructure from the ground up as General Manager and Director at Orthogonus Technologies.

At Princeton Medical Systems, John leads proof-of-concept development, strategic planning, and institutional collaborations at the intersection of healthcare technology and clinical research.

Our Principles

What Drives Us

Data Quality Over Quantity

A smaller, meticulously validated dataset outperforms a massive, noisy one. We optimize for clinical accuracy, not volume.

Compliance By Design

Regulatory alignment isn't an afterthought — it's built into every stage of our data pipeline, from ingestion to export.

Open Ecosystem

Our certified datasets integrate seamlessly with MONAI, nnU-Net, and Hugging Face — no vendor lock-in, just better data.

Join Us

We're building something meaningful at the intersection of AI and healthcare. If you're passionate about medical imaging, data quality, or healthcare technology, we'd love to hear from you.

careers@princetonmedicalsystems.com