Paul Aljabar

Paul Aljabar


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Personal profile

Research interests

My research centres on developing algorithms for analysing medical images of the brain such as MR data. The main goal is to characterise salient features of the anatomy and the development or degeneration of the brain. I am interested in combining the established and fundamental tools of medical image processing, such as registration and anatomical segmentation, with machine learning methods in order to develop novel methodologies for group and longitudinal studies using MR data sets. The ultimate aim of such studies is to provide population-level representations that are relevant to clinical and neuroscientific hypotheses. In particular, I am keen on finding out how fundamental medical image processing methods may be informed by, as well as help create, population-level representations.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Doctor of Philosophy, Tracking Longitudinal Change Using MR Image Data, Imperial College London

Award Date: 1 Jan 2007


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