Develop multi-modality cardiopulmonary computational models for pulmonary hypertension

Pulmonary hypertension (PH) is a severe progressive disease affecting both the heart and lungs, and a range of imaging techniques are utilised to phenotype PH and direct patient management to improve disease prognosis. A major challenge for implementing the cardiac and pulmonary computational models developed at the Auckland Bioengineering Institute in PH patients is that the current models rely on different imaging modalities. A new exciting collaboration with the Sheffield Pulmonary Vascular Disease Unit, a specialist referral centre for treating PH in the UK, will provide access to a registry of over 1000 PH patients assessed with a variety of standard and novel imaging techniques. This comprehensive PH imaging data will facilitate the development of new patient-specific computational models of coupled heart and lungs systems based on multi-modality PH imaging. Additional aims for this PhD project include:

• Develop a framework for spatial co-registration across different imaging modalities to reconcile structure and function information from multi-modality heart and lung imaging. 
• Develop machine learning-based segmentation approaches to accelerate cardiopulmonary image processing methods and pipelines.
• Validate the newly developed cardiopulmonary computational models by implementing them within a New Zealand-based clinical workflow for PH disease management.
  

• Bachelor’s or Masters degree in Engineering, Physics or equivalent.
• Experience in medical imaging, image processing and mathematical modelling would be desirable

Aotearoa Fellowship