The CliniFace project aims to deliver a suite of software tools packaged within a single overarching application named 3D-FAST (3D Facial Analysis Streamlining for clinical Translation).

The vision for 3D-FAST is to quickly and accurately analyse a 3D scan of a patient’s face (as captured by existing photogrammetric hardware) to provide a summary to a clinician. The result is a series of facial characteristics that are likely to suggest of some underlying genetic condition. 

Thirty per cent of rare diseases patients wait up to 30 years for a diagnosis. Thirty per cent see six or more doctors before receiving a diagnosis and nearly fifty per cent receive an initial diagnosis that is incorrect.  3D-FAST is expected to significantly improve upon existing methods of automated facial analysis for assisting in syndromic diagnosis, especially in the realm of rare disease diagnosis where there is limited clinical data.

This stage of the project aims to answer two key research questions:

  • Is it possible to accurately classify syndromes and Human Phenotype Ontology (standard for describing human variation) terms from 3D scans of a patient’s face?
  • Are there inferential associations between a patient’s genetic information and their facial (dys)morphology (abnormal features)?

In order to answer these questions researchers will extend the 3D-FAST capabilities to include several critical features such as facial co-registration, facial averaging, analysis of facial differences and symmetry, and detection and classification of salient facial morphological characteristics. 

This innovative research has led to real-time data mining for comparisons with a repository of facial imagery for powerful diagnostic and treatment monitoring. In time, it will significantly improve clinical efficiency and patient outcomes.

The next development phase of CliniFace includes growing a database of facial imagery that clinicians can utilise and compare captured faces and facial landmarks against normalised faces in determining disease types. Future collaborations include the Fiona Wood Burns Unit and research into Down’s Syndrome and Foetal Alcohol Syndrome.


3D-FAST facial analysis tool assists a world-first study to unlock the mystery of rare diseases. Watch the recent news story here.

Project Partners

Department of Health (WA) – Genetic Services WA – Curtin University – Princess Margaret Hospital Foundation

Project Leaders

gareth BaynamDr Gareth Baynam
Department of Health (WA)


WA Curtin PetraHelmholzDr Petra Helmholz
Curtin University