We curate radiologist-annotated lung CT and chest X-ray datasets that AI teams use to train, validate, and deploy clinical imaging models. We also provide the DICOM infrastructure tools to prepare, convert, and protect that data — end to end.
The Data Behind Better Medical AI
Princeton Medical Systems is a medical imaging data and AI infrastructure company. We specialize in curating radiologist-annotated datasets from lung CT and chest X-ray studies — the clinical-grade training data that AI development teams need to build imaging models that actually perform in the real world.
Our DICOM tooling handles the data preparation layer: format conversion, de-identification, and packaging — so researchers and engineers can focus on model development, not data wrangling
Through our Talent Pipeline programs, we also train the next generation of medical imaging engineers — equipping students and early-career professionals with practical Python and deep learning skills specific to clinical imaging.
Every dataset we deliver is annotated by qualified radiologists following structured labeling protocols — built to our PMS Imaging Standard™ for clinical-grade quality.
Our format conversion and de-identification tools plug into existing AI development pipelines, giving engineering teams clean, analysis-ready imaging data without custom preprocessing overhead.
From raw DICOM to ML-ready datasets — we handle every step of the medical imaging data lifecycle.
Convert medical images across 10+ format pairs — DICOM, NIfTI, NRRD, TIFF, JPEG, VIDEO, HDF5 — to fit any downstream workflow or archive requirement.
Automatically strip or pseudonymize patient identifiers from DICOM files — enabling privacy-compliant dataset sharing for research, multi-site collaboration, and AI training.
Built for the Teams Who Build Medical AI
AI developers and research teams need imaging data they can trust — annotated correctly, de-identified properly, and delivered in formats their pipelines can use. That’s exactly what we do, with the rigor that clinical-grade data demands.
Every annotation in our datasets is reviewed and signed off by qualified radiologists. Our PMS Imaging Standard™ defines the labeling protocol, ensuring your training data is consistent, reproducible, and clinically meaningful.
We focus specifically on thoracic imaging — lung CT and chest X-ray. Depth of specialization produces better annotations, more consistent labeling schemas, and datasets that are directly applicable to pulmonology and oncology AI workflows.
From raw DICOM acquisition through format conversion, de-identification, annotation, and ML-ready packaging — our tools and services cover the full imaging data pipeline, so you don't need to stitch together multiple vendors.
Our Talent Pipeline programs train early-career engineers in medical imaging AI — Python, DICOM, and deep learning for clinical imaging. We're building the technical workforce this industry needs
Latest Blogs & News
AI in Fusion Of Pathomics, Radiomics, And Genomics in Lung Cancer 1. Introduction The fusion...
Transforming Diagnostics for the Future 1. Introduction Artificial Intelligence (AI) is revolutionizing medical imaging, enhancing...
Princeton Medical Systems pioneers AI-driven medical imaging solutions, enhancing diagnostics and empowering healthcare professionals with cutting-edge technology.
