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CHIC: Assessing the role of deep-learning in image-analysis of biosensing colour changing elements


Project Description

Connected Health Innovation Centre:
In 2013 Invest NI committed to create a number of multi-million-pound business research centres, in key business areas, through the establishment of industry led competence centres. The Connected Health Innovation Centre (CHIC) is a competence centre that focuses on the Connected Health market. In 2019 Invest NI extended the support of CHIC through funding for a further 3 years. This funding supports a number of strategic research projects as well as Doctoral research in order to ensure research produced by CHIC advances the state of the art.
Connected Health embraces a number of areas and focuses on the use of technology to improve health care. It will utilise technology to provide opportunities for care provision, diagnostics and support beyond the hospital setting.
This studentship will reside within the School of Engineering, Faculty of Computing, Engineering and the Built Environment at Ulster University based at the Jordanstown campus. The project is fully aligned with the research strategy of CHIC.

Project Summary:
Lateral flow diagnostic paper based biosensors are widely available as a low cost and rapid method of screening a patient’s health condition before referring for full lab based assessment. These paper based sensors rely on gold colloid conjugate systems that densify as a response to analyte concentrations thus providing a colour change, whereby the levels of intensity can be calibrated to produce a quantitative and qualitative sensing mechanism. Imaging this colour change by a CMOS camera with suitable illumination provides large data sets that require image analysis, digital signal processing and artificial intelligence techniques which in turn will help with the overall sensitivity, specificity and ultimately the number of false positives / false negatives. This PhD will explore suitable image techniques and appropriate deep learning techniques to address the need for improved analysis of the compound raw data that such a CMOS camera sensor outputs. The project will focus on cardiac and associated biomarkers but will mainly address computational approaches to the data.

Funding Notes

This project is funded by: Invest NI Connected Health Innovation Centre

Invest Northern Ireland is acknowledged for supporting this project under the Competence Centre Programme Grant RD1014267- Connected Health Innovation Centre.

Funding will cover all fees and a generous stipend for the successful candidate throughout the three years of study.

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