Research Theme: Image Computing and Computational Modelling (pre-2019)
Learning optimal image representations for MRI reconstruction, synthesis and analysis
1st supervisor: Jo Hajnal, King’s College London 2nd supervisor: Daniel Rueckert, Imperial College London The aim of the project is to develop machine learning approaches for the reconstruction, synthesis and analysis of MR images. In particular, we aim to...read moreReal-time assessment of coronary haemodynamics via hybrid fluid dynamics & machine learning approach
1st supervisor: Jack Lee, King’s College London 2nd supervisor: Andy King, King’s College London The aim of the project is to develop a non-invasive computational diagnosis pipeline for assessing the severity of coronary lesions that could easily be...read moreAutomated assessment of fetal movements as an indicator of postnatal neurological health and function
1st supervisor: Bernhard Kainz, Imperial College London 2nd supervisor: Jo Hajnal, King’s College London Neonatal movements are commonly assessed as a way of predicting neurological function of the baby, but methods currently in use are subjective,...read moreLearning the signature of disease in echocardiography
1st supervisor: Pablo Lamata, King’s College London 2nd supervisor: Andy King, King’s College London The objective is the development and validation of methodology that automatically extracts diagnostic and prognostic biomarkers from echocardiographic...read moreLoad More