Postgraduate DiplomaHealth, Biomechanics, Wearables & Operational Safety Applications open

Postgraduate Diploma in Radiomics and Risk Models

Online 800 h Postgraduate Diploma in radiomics and risk models. 8 modules with IBSI (Image Biomarker Standardisation Initiative), TRIPOD+AI (reporting of predictive models) and PyRadiomics. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma

Postgraduate Diploma in Radiomics and Risk Models — studying from New Zealand

Health engineering in New Zealand covers medical devices, biomechanics, rehabilitation technology and occupational safety, with significant activity in Auckland, Wellington and Christchurch. The Medsafe regulator within the Ministry of Health oversees medical device approval, and the Accident Compensation Corporation plays a central role in workplace injury prevention and safety. Biomechanics research is supported by university groups and by the country's strong sports science community.

Fees for New Zealand: NZ$2,550 (New Zealand dollar), with instalments and employer sponsorship available.

Relevant bodies in New Zealand

  • Medsafe (New Zealand Medicines and Medical Devices Safety Authority)
  • WorkSafe New Zealand
  • Accident Compensation Corporation (ACC)

Typical roles

  • Biomedical Engineer
  • Medical Device Engineer
  • Biomechanics Engineer
  • Occupational Safety Engineer

Questions from New Zealand

Will this qualification be recognised by Engineering New Zealand in New Zealand?

Engineering New Zealand is the professional body for engineers here and runs the Chartered Professional Engineer (CPEng) pathway. SEIUM's qualifications are private qualifications, not official state degrees, and are not accredited by any national body. Recognition for any purpose is decided by the employer or the relevant body, so check with them before relying on it for registration.

Would a biomechanics or wearables background help me find work in New Zealand?

Interest in wearables and workplace safety exists across New Zealand's health technology, rehabilitation, sport science and occupational health sectors. Whether an employer values a SEIUM qualifications depends on the employer's own assessment of your skills and experience. A portfolio of applied projects is often what carries the most weight in hiring decisions.

Can I study this while working full time in New Zealand?

Yes. The programme is fully online and taught in English, so you can study from anywhere, including from home, and you do not need a student visa for that. Master's programmes total 1,900 hours, postgraduate diplomas 800 hours and specialist courses 300 hours, with an assigned technical tutor. Fees can be paid in instalments, and employer sponsorship is possible.

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Learning outcomes

What you will be able to do

01

Describe quantitative medical imaging and its sources of variability.

02

Segment regions of interest in a reproducible way.

03

Extract IBSI-compliant radiomic features.

04

Harmonise multicentre data and assess its robustness.

05

Select variables and train predictive models while avoiding overfitting.

06

Build risk and survival models.

07

Validate radiomic models and assess their clinical utility.

Profile

Who it's for

  • Data scientist in medical imaging who wants to specialise in Radiomics and Risk Models.
  • Medical physicist who wants to specialise in Radiomics and Risk Models.
  • Radiomics researcher who wants to specialise in Radiomics and Risk Models.
  • Biostatistician who wants to specialise in Radiomics and Risk Models.
  • Clinical AI engineer who wants to specialise in Radiomics and Risk Models.
  • Research radiologist who wants to specialise in Radiomics and Risk Models.
  • Engineering or science graduates looking to enter hospitals.
Standards & tools

What you'll work with

  • IBSI (Image Biomarker Standardisation Initiative)
  • TRIPOD+AI (reporting of predictive models)
  • DICOM
  • Radiomics Quality Score (RQS)
  • Regulation (EU) 2024/1689 (Artificial Intelligence)
  • Regulation (EU) 2017/745 (MDR)
Syllabus

8 modules · 800 h

  1. 1.1CT physics: Hounsfield units and reconstruction
  2. 1.2MRI sequences and intensity heterogeneity
  3. 1.3PET and standardised uptake values (SUV)
  4. 1.4DICOM format and relevant metadata
  5. 1.5Effect of acquisition parameters on measurements
  6. 1.6Calibration phantoms and quality control
  7. 1.7Preprocessing: resampling, normalisation and discretisation
  8. 1.8Public repositories: TCIA and LIDC-IDRI
  9. 1.9Anonymisation of imaging studies
  10. 1.10Laboratory: reading and resampling DICOM series with Python
  1. 2.1Manual segmentation and inter-observer variability
  2. 2.2Semi-automatic methods: thresholding and region growing
  3. 2.3Deep segmentation with U-Net and nnU-Net
  4. 2.4Overlap metrics: Dice and Hausdorff distance
  5. 2.5Mask formats: RTSTRUCT, NIfTI and DICOM SEG
  6. 2.6Tools: 3D Slicer and ITK-SNAP
  7. 2.7Peritumoural and habitat segmentation
  8. 2.8Effect of segmentation on feature stability
  9. 2.9Radiological review of contours
  10. 2.10Practical: segmentation of lung nodules in 3D Slicer
  1. 3.1Three-dimensional shape and size features
  2. 3.2First-order histogram statistics
  3. 3.3GLCM, GLRLM and GLSZM texture matrices
  4. 3.4NGTDM and GLDM matrices
  5. 3.5Wavelet and Laplacian of Gaussian filters
  6. 3.6Standardisation under the IBSI initiative
  7. 3.7PyRadiomics library and its configuration
  8. 3.8Delta-radiomic features in longitudinal studies
  9. 3.9Deep features versus handcrafted features
  10. 3.10Laboratory: extraction with PyRadiomics on a public cohort
  1. 4.1Test-retest reproducibility of features
  2. 4.2Intraclass correlation coefficient and agreement
  3. 4.3Scanner and acquisition protocol effects
  4. 4.4Statistical harmonisation with ComBat
  5. 4.5Image and mask perturbations
  6. 4.6Filtering unstable features
  7. 4.7Radiomic quality according to the RQS score
  8. 4.8CLEAR guideline for reporting radiomic studies
  9. 4.9Multicentre studies and batch bias
  10. 4.10Practical: stability analysis with contour perturbations
  1. 5.1High-dimensionality and small-sample problem
  2. 5.2Reduction by correlation and redundancy
  3. 5.3LASSO regression and elastic net
  4. 5.4Random forest and gradient boosting
  5. 5.5Support vector machines
  6. 5.6Nested cross-validation and data leakage
  7. 5.7Class imbalance and resampling
  8. 5.8Integration with clinical and genomic variables
  9. 5.9Interpretability with SHAP values
  10. 5.10Workshop: LASSO model for malignancy prediction
  1. 6.1Survival analysis and Kaplan-Meier curves
  2. 6.2Cox regression and the proportional hazards assumption
  3. 6.3Random survival forests and DeepSurv
  4. 6.4Concordance index and time-dependent AUC
  5. 6.5Calibration and calibration plots
  6. 6.6Decision curves and net benefit
  7. 6.7Radiomic-clinical nomograms
  8. 6.8Stratification into risk groups
  9. 6.9TRIPOD+AI guidelines for prediction models
  10. 6.10Case study: prognostic radiomic signature in lung cancer
  1. 7.1Internal, temporal and external validation
  2. 7.2Risk of bias with PROBAST
  3. 7.3Data drift after deployment
  4. 7.4Integration into PACS and radiological workflow
  5. 7.5MDR requirements for diagnostic software
  6. 7.6EU AI Regulation and high-risk systems
  7. 7.7Explainability for clinicians and patients
  8. 7.8Impact assessment on clinical decision-making
  9. 7.9Publishing reproducible code and models
  10. 7.10Case study: external validation plan for a published model
  1. 8.1Clinical question and definition of objective
  2. 8.2Cohort selection and curation
  3. 8.3Segmentation protocol and quality control
  4. 8.4Feature extraction and harmonisation
  5. 8.5Variable selection and training
  6. 8.6Assessment of discrimination and calibration
  7. 8.7External validation and interpretation
  8. 8.8Report in line with CLEAR and TRIPOD+AI
  9. 8.9Dissertation and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is PyRadiomics, 3D Slicer, LIFEx, R (survival), scikit-learn, in free, academic or evaluation versions. Studies are examined using real radiomic extraction procedures in retrospective cohorts, test-retest reproducibility studies and multicentre external validation. Assessment is continuous, module by module, plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test bench, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven final project:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible delivery(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:with a safety-by-design approach, cyber-OT, DIH and compliance as core pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Clinical question and definition of objective

Describe quantitative medical imaging and its sources of variability.

Cohort selection and curation

Segment regions of interest in a reproducible way.

Segmentation protocol and quality control

Extract IBSI-compliant radiomic features.

Feature extraction and harmonisation

Harmonise multicentre data and assess its robustness.

Variable selection and training

Select variables and train predictive models while avoiding overfitting.

Career opportunities

Where this takes you

Data scientist in medical imagingMedical physicistRadiomics researcherBiostatisticianClinical AI engineerResearch radiologist
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. No university degree is required.
  • Internet connection and a computer capable of running the programme's software.
  • A level of Spanish sufficient to follow technical regulatory texts.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

FAQ

Frequently asked questions

The programme comprises 800 hours in total, spread over 6 to 8 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.

You work with PyRadiomics, 3D Slicer, LIFEx, R (survival), scikit-learn. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

An own-award diploma from the SEIUM Institute upon passing continuous assessment and the integrative project. This is in-house training, not an official Ministry qualification.

Yes. Modules passed in a course or Postgraduate Diploma in the same area are credited towards the advanced programme. Check the credit transfer policy when you enrol.

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