Electrical Impedance Spectroscopy (EIS) is a method for identifying different tissue types by its passive electrical characteristics measured over a range of AC frequencies. It has been successfully used to identify early cancers in the cervix (Zedscan, University of Sheffield, Zilico), and early data suggests that it may be applicable as a tool to guide surgical intervention in thyroidectomy by discriminating between visually similar tissue types.
This project aims to use both machine learning on an existing data set, collected during surgery and finite element simulation techniques to answer the following questions:
i) Which characteristics of the impedance spectrum give best discrimination between the tissue types?
ii) What are the characteristics of the tissue that give rise to these features? This will ultimately support the design of a commercially guided instrument for EIS-guided surgery.
Dr Dawn Walker, Department of Computer Science and Insigneo
Professor Keith Hunter, Academic Unit of Oral and Maxillofacial Medicine, Surgery and Pathology, School of Clinical Dentistry and Insigneo
Industrial Partner, Zilico Ltd – https://zilico.co.uk/
Competition funded project (UK students only)
How to apply?
To apply for the studentship, applicants need to apply directly to the University of Sheffield using the online application system. Please name Dr Dawn Walker as your proposed supervisor. Complete an application for admission to the standard Computer Science PhD programme http://www.sheffield.ac.uk/postgraduate/research/apply Applications should include a research proposal, CV, transcripts and two references. The research proposal (up to 4 A4 pages, including references) should outline your reasons for applying for this scholarship and how you would approach the researching, including details of your skills and experience
For further information: Please contact Dr Dawn Walker email@example.com