Taught on VIDS — the Verified Imaging Dataset Standard
Medical Imaging AI Bootcamp
Learn. Build. Apply. A four-day, hands-on certification program that takes you from DICOM files to a documented, evaluated, regulator-ready imaging AI project — built on public, de-identified clinical datasets.
Who Should Attend
Built for people moving into medical imaging AI
Basic Python is required. No prior medical imaging experience is needed.
Engineers & data scientists
Moving into healthcare and needing to work confidently with real imaging data, clinical workflows and regulatory expectations.
Clinicians & radiology professionals
Who want to understand how imaging AI is built, evaluated and validated — and what to ask of the tools they use.
Researchers, students & CRO / pharma teams
Working with imaging endpoints, datasets or AI-assisted reads who need provenance and reproducibility done properly.
Curriculum
Four days, eleven modules
Foundations → Data → Models → Quality & Trust. Each day builds on the last, and every day includes hands-on lab work.
1.1 DICOM Structure & Standards
How DICOM files are organised: tags, metadata, and the patient–study–series hierarchy.
1.2 Working with CT and MRI
Hands-on with real CT and MRI studies: loading, viewing and handling imaging data.
1.3 PACS Systems
How hospitals store and move images, and where AI fits into the clinical workflow.
2.1 Anonymisation & De-identification
Removing patient-identifying information from imaging data before it is used.
2.2 Dataset Curation
Selecting, organising and preparing imaging data into a usable dataset.
2.3 Annotation Workflows
How images are labelled to create ground truth for training AI models.
3.1 Segmentation Models
AI models that outline structures and findings in medical images.
3.2 MONAI / PyTorch Ecosystem
Building medical imaging AI with the MONAI framework on PyTorch.
4.1 Dataset QC
Checking datasets for errors, gaps and inconsistencies before they reach a model.
4.2 Bias Risks
Where bias enters imaging datasets and models, and how to recognise it.
4.3 Reproducibility
Documenting data and experiments so results can be repeated and verified, framed on VIDS.
Included
What's included
Prerequisites
What you'll need
Faculty
Learn from the team behind VIDS
Co-Founder & CTO, Princeton Medical Systems
Udemy instructor · 4.5+ rated courses
Co-Founder & COO, Princeton Medical Systems
Fees & Registration
Reserve your seat
Fill in a short registration form, then pay securely with Razorpay. Your seat is confirmed on successful payment: you receive a payment receipt by email immediately, and joining details within 2 business days of payment and again before Day 1.
Program fee
23–26 October 2026 (Fri–Mon) · 7:00 PM – 10:00 PM IST each evening · Online, live · 15 seats
By registering you agree to our Terms of Service, Privacy Policy, Cancellation & Refund Policy and Service Delivery Policy.
Payments are received by Princeton Medical Systems.
FAQ
Frequently asked questions
Do I need medical imaging experience?
No. Day 1 starts from the fundamentals of DICOM and AI/ML. You do need basic Python.
Which certificate will I receive?
There are two levels, both issued as e-certificates by Princeton Medical Systems. Participants who attend all four live sessions receive the Course Completion Certificate. Those who also complete the capstone project (the cohort you curate, model and document across Days 2–4) receive a combined Course & Capstone Project Completion Certificate.
Which datasets will we use?
Only public, de-identified datasets. No patient data from any hospital is used or required.
What if I can't attend after paying?
Cancel at least 2 business days before the first session (for this cohort, by 7:00 PM IST, Wed 21 Oct 2026) for a full refund of the amount paid, including GST. After that, fees are not refundable. If we cancel or reschedule, you can choose a full refund. See the Cancellation & Refund Policy.
Will I get a GST invoice?
Yes, on request. The fee includes GST. Email us with your Razorpay payment ID, and for an invoice in your organisation's name include its registered name and GSTIN.
Can my organisation register several people?
Yes — contact us for group registration.