Analysing brain and muscle
Dr Diwei Zhou's research involves developing novel statistical methods and tools for analysing the structure of brain white matters and skeletal muscle tissues using data from Diffusion Tensor Imaging (DTI).
DTI is a non-invasive Magnetic Resonance Imaging (MRI) modality which provides a unique insight into biological tissue structure and organisation of the human body. DTI has been applied to reveal subtle abnormalities in a large number of brain diseases and disorders including multiple sclerosis, stroke, schizophrenia and dyslexia. Another promising application of DTI is fibre tracking. The ability of fibre tracking to visualise anatomical connections between different parts of the brain, in vivo, non-invasively and on an individual basis, has emerged as a major breakthrough for neurosciences.
Musculoskeletal (MSK) conditions have an enormous impact on the quality of life of millions of people in the UK. Around 9.6 million adults and 12,000 children in the UK were suffering from musculoskeletal conditions in 2011. Although DTI has been widely used to study the white matter of the brain, MSK DTI is still in its infancy. There is an urgent need for statistical methods and computing tools for DTI image analysis. Extracting information from DTI presents challenges because the DTI data has a complex mathematical structure and is also prone to noise and artefacts. This task is even more challenging when considering skeletal muscle tissue due to the complexity of these tissues where they cross, kiss and branch.
Dr Zhou’s work on non-Euclidean statistics for DTI has substantially improved diffusion tensor data analysis from MRI experiments. A DTI software tool for MSK DTI analysis is under development by Dr Zhou’s team with collaborative support from clinical experts at Guy’s and St. Thomas Hospitals (London) and Queen’s Medical Centre (Nottingham). Once validated, this tool will have national and global impacts on economy, skills, society and knowledge.
Dr Diwei Zhou is a Senior Lecturer in Statistics. Her main area of research has been the development of statistical methodology for large and highly structured data analysis with applications to neuroscience, sport science, chemistry, engineering and computer science.