About the project
In this unique PhD project, we aim to develop advanced AI models for creating cardiac digital twins such as virtual heart models. We will employ the dataset (imaging, ECG, electronic medical records, etc) collected from the patients, to accurately modelling the anatomy and simulate the function of patients' diseased hearts. These models, coupled with machine learning techniques, contribute to the identification of crucial mechanistic relationships and features that offer insights into the trajectory of a patient's heart condition.
The research will delve into the intersection of AI and cardiac sciences, exploring novel approaches to revolutionize our understanding of the human heart. With the potential to impact medical treatments and technology advancements, this project promises an exciting and important avenue for personalized medicine.
The project will collaborate with a multi-disciplinary team, including academics from the University of Southampton and experts from University of Oxford, Imperial College London, Fudan University, etc.
You will use the following techniques:
- Image analysis to create 3D anatomical model from medical imaging, using image segmentation and mesh reconstruction.
- Electrophysiological modelling to simulate the electrical activity in the heart, using monodomain/ bidomain model, Aliev-Panfilov model and Eikonal model.
- Machine learning to establish deep learning models for cardiac modelling and simulation, using multi-modal fusion and physics-informed model.
