Example research and industry projects

Healthcare: From cemetery to clinic

Digitised pathological data from archaeological leprous skeletons

The project was based at the University of Bradford, and is the result of a fruitful collaboration between Archaeological Sciences and the Centre for Visual Computing.  It was led by Dr Andrew Wilson, and including Dr Jo Buckberry, Professor Hassan Ugail, Dr Christopher Gaffney, Dr Christopher Watkins, Mr Andy Holland, Mr Tom Sparrow, and Dr Rebecca Swift.

Leprosy is a debilitating disease with a strong social stigma. Once common throughout the old world, it is still encountered in the developing world. The project aimed to digitise data pertaining to leprous medieval skeletons and clinical x-rays of modern sufferers in order to allow medical historians, palaeopathologists, clinicians and the interested public to observe and better understand the skeletal lesions of the disease, how they manifest across the skeleton and how they arise. This links to another aim of the project which was to inspire an emotional response from the wider public. This was achieved by offering people the change to come face-to-face with the realities of the disease and it provided the opportunity to gain insight into how people in the past may have responded to the social stigma of the disease.

3D laser scans of affected bones from the medieval leprosarium of St. James and Mary Magdalene, Chichester, alongside digitised x-rays of these individuals and those of clinical cases were disseminated via an interactive GIS cemetery plan and associated database, with pathological descriptions. The project required rapid digitisation to ensure the sustainability of this unique, but extremely fragile collection.

Healthcare: Predicting how tablets crush

One way to improve the design of pharmaceutical tablets is to understand how they'll break down under physical pressure. In this study, working with another University department, we created a computer simulation to model how different sizes and shapes of tablet behave when crushed.

The aim was to develop a computer based simulation platform to study the crushing behaviour of Pharmaceutical Tablets working with the Institute of Pharmaceutical Innovation, University of Bradford.

Using mathematical modelling we developed a computer platform that can predict the crushing behaviour of a typical pharmaceutical tablet. The computer model has been tested and validated using real data supplied by the Institute of Pharmaceutical Innovation.

The platform enables to predict the crushing behaviour of tablets and would enable better design of tablets.

Healthcare: Automated analysis of digital mammograms

Breast cancer screening is currently carried out by radiologists, who have to individually examine each result. What if an automated computer analysis could accurately detect abnormalities instead, cutting workload and speeding up diagnosis?

A Computer Aided Diagnosis (CAD) is designed to reduce the workload of radiologists by offering automatic detection, verification and/or classification of abnormalities in digital mammogram images such as microcalcifications, circumscribed masses and speculated lesions.

The development of a computerised CAD system with advanced features to accurately detect the abnormal structure in mammograms and to provide accurate measurements of the size and the location of tumours.

Healthcare: Analysing 3D images of skin and wounds

This provides advantages to both health care workers and patients if damaged skin can be measured and evaluated automatically, non-invasively, using a 3D visual recognition process.  The aim was to develop a computer-based platform for accurately measuring the properties of skin and wounds for Bradford Royal Infirmary (Proof of Concept).

We developed a non invasive computer-based platform that can analyse 3D images of skin and wounds, in order to characterise both the skin and the wounds. In particular, based on the information provided in 3D images we can automatically calculate the surface area and volume of the wound.

The system can accurately undertake essential measurements of skin and wounds to enable health care workers to evaluate the available therapies.

Healthcare: Intelligent Analysis of EEG signals

The Advanced Digital Institute (ADI) developed a new system for measuring biosignals from the heart ( ECG, or electro cardiogram), muscles (EMG, or electro-myogram), the brain ( EEG, or electro-encephalogram) and the gavlanic skin response (GSR).

The main goal of this project was to understand and extract patterns of the sensors, the EEG in particular, and understand actions that affects this signal in order to quantify awareness.

Thus far this collaboration has developed novel processing and machine learning approaches to analysing and classifying the biosignals generated by ADI's biosensors.

Healthcare and security: Predicting human facial ageing

There are plenty of applications for the science of accurately forecasting how human faces will look after years of ageing. It's not just the passage of time that can be simulated: health care professionals can also use our platform to demonstrate how the changes are excpected to differ with a variety of lifestyle factors.

The aim was to develop a computer based simulation platform for simulation of human facial ageing based on 3D scan data of faces. It was funded by Engineering and Physical Sciences Research Council (EPSRC).

We developed a computer based platform for prediction of human facial ageing. Based on 3D scan data of a given face human face our platform can predict the age of the person and can predict the facial changes as the person ages. The system can also predict the facial changes due to other external factors such as smoking and use of drugs.