Functional Brain Image Understanding for Differential Diagnosis of Dementia


Intelligent analysis of functional brain images and extraction of pathologic patterns from large-group study for early diagnosis of dementia types


Professor David Feng, Dr Yong Xia

Research Location

Computer Science

Program Type



With the increasing ageing of the population, dementia has become an important world-wide public health problem. Even though no definitive cure has been found for this disease, early diagnosis is useful for choosing appropriate management and developing new treatment, which can effectively slow-down the progression of dementia. Functional imaging techniques of positron emission tomography (PET) is able to detect subtle changes in cerebral metabolism before there are changes on anatomical imaging and before a clinical diagnosis of probable dementia can be made. This ability gives PET a distinct advantage over anatomical imaging techniques in the evaluation of neurodegenerative disorders like dementia at the early stages of the disease process. However, since the functional changes in the early course of dementia can be subtle, there are some overlapped patterns in images of different dementia types and lacks of clearly defined boundaries between dementia patients and normal aged controls. This project aims to develop a functional brain image understanding system, with the identification and extraction of intrinsic pathologic patterns via analysing a large group of brain PET studies, to provide discriminatory classification of dementia types, and to offer computer-aided early diagnosis of dementia through case-based reasoning or evidence-based medicine.

Want to find out more?

Contact us to find out what’s involved in applying for a PhD. Domestic students and International students

Contact Research Expert to find out more about participating in this opportunity.

Browse for other opportunities within the Computer Science .


Functional brain imaging, dementia, image analysis, Image understanding, pattern classification

Opportunity ID

The opportunity ID for this research opportunity is: 1195

Other opportunities with Professor David Feng

Other opportunities with Dr Yong Xia