- Brain tumours are the most common solid tumours in childhood and the largest cause of death from cancer in this age group
- Being able to classify a brain tumour’s type, without the use of biopsy, is hard to do; however diffusion weighted imaging, an advanced imaging technique, when combined with machine learning, can help a UK-based multi-centre study, including WMG, University of Warwick has found.
- Being able to characterise the tumour(s) faster and more accurately means they can be treated more efficiently
Diffusion weighted imaging and machine learning can successfully classify the diagnosis and characteristics of common types of paediatric brain tumours a UK-based multi-centre study, including WMG at the University of Warwick has found. This means that the tumour can be characterised and treated more efficiently.
Our Associate Professors Jerome Charmet and George Despotou deliver the first WMG Associate Professor Lecture Series
Jerome will be giving an overview of his current activities, concentrating on two precision oncology projects. Jerome has worked with a company and clinicians to develop two devices that can simplify cancer management and in particular immunotherapies.
George will present his lecture on "The digital health transformation: at the crossroads of science, engineering and medicine.": Healthcare has experienced a profound transformation. This has been made possible by numerous applications that change the way one will interact with the healthcare system. Knowledge from biology, engineering, computer science, medicine, as well as knowledge from multiple domains such as aerospace and automotive, is brought together in digital health. This results in building safe, effective and efficient patient-centric services and empowering the patient to manage their daily care. The presentation gives an overview by examples, of digital health as the crossroads multiple disciplines.
To find out more about the lecture series have a look at the following link
Back in March we shared this exciting story thanks to our colleagues at the Institute of Digital Healthcare, WMG. The advent of consumer virtual reality technology combined with 3D motion capture allows real movements to be accurately translated onto an avatar that can be viewed in a virtual environment. Our Researchers investigated whether this technology can be used to provide guidance to physiotherapy patients, by providing a virtual physiotherapist in the home to demonstrate the prescribed exercises.
- Current Physiotherapy techniques require patients to complete exercises at home, which doesn’t include much guidance.
- Virtual reality (VR) combined with 3D Motion capture could allow movements to be translated onto an avatar the patient can follow, thanks to researchers at WMG.
- Consumer VR technologies can be used for both providing guidance to physiotherapy exercises, but also to make the exercises more interesting and encourage people to complete the course they need Virtual reality could help physiotherapy patients complete their exercises at home successfully thanks to researchers at WMG, University of Warwick, who managed to combine VR technology with 3D motion capture.