Artificial Intelligence for Diagnostic Predictors of Aortic Disorders (AIDA)


Aortic dissection and aneurysm rupture are time-critical medical emergencies and therefore assessment of cardiovascular images is a critical and time-sensitive. It is a labor intensive, time consuming and a subjective process. Aortic dissection is the only cardiovascular condition to have no improvement in survival rate over the last 4 decades. For instance, in Aortic disease patients, post Endo-Vascular Aortic Repair (EVAR) there is an exhaustive annual follow-up which requires analysing Computed Tomography Angiography (CTA) and requires significant manual analysis of the medical images. The aim of this project is to implement deep learning techniques in cardiovascular 1) image segmentation to detect aortic dissection and 2) blood flow modelling using Physics Informed Neural Networks which could have the potential to predict biomechanical indicators in real time in event of an adverse aortic event. 

Principal Investigators:

Prof. Abhay Pandit, Ms. Niamh Hynes, Dr. Bharat B. Tripathi, Dr. Andy Donald, and Prof. Edward Curry 

Funded by: