PhD Studentship: Towards accurate diabetic foot ulcers quantification using novel multimodal dataset

FUNDED PHD OPPORTUNITY

Summary

The management of chronic wounds poses a considerable burden on healthcare systems, with approximately 2.2 million patients currently afflicted, resulting in an annual cost of £5.3 billion for the NHS to address wound care and its associated comorbidities, including amputations.

The logistical challenges of transporting vulnerable patients to and from hospitals incur additional costs and elevate the risk of infections, leading to a significant rise in patient mortalities. Addressing this complex scenario necessitates an accurate and automated computerised solution for measuring and characterising wound areas, which is currently non-existent.

This research project aims to develop an innovative digital technology solution to enhance clinicians’ confidence in monitoring wounds and facilitating remote assessment and monitoring. By enabling at-home tracking, the system aims to encourage more regular checks and prompt responses to declines in recovery, ultimately fostering early intervention.

This approach contributes to reducing healthcare costs and engenders greater trust in digital technology among end-users, thereby enhancing overall patient care- the collaborative development of this system with renowned researchers in the field of AI for wound monitoring and a chance to work with clinical and industrial partners.

Aims and objectives

The proposed research project aims to design innovative multimodal intelligent techniques to measure diabetic foot ulcers and wounds accurately. The research objectives are to:

• Create a world-leading multi-modal digital wound repository.
• Design an innovative 2.5D modelling tool for wound assessment.
• Create a novel algorithm using a multimodal dataset to improve the accuracy of predicting ulcer/wound healing.

Specific requirements of the project 

Successful candidates would have a strong background in Computer Science, Engineering, Maths or Physics, and preference would be given to those with a good understanding of computer vision and deep learning.

It is essential to have good background knowledge in machine learning, computer programming, and a proactive approach to their work. 

A self-motivated, driven, and creative individual will push the bounds of existing research by our world-leading team:

• Yap, M.H., Kendrick, C. and Cassidy, B. eds., 2023. Diabetic Foot Ulcers Grand Challenge: Third Challenge, DFUC 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings (Vol. 13797). Springer Nature.

Student Eligibility

Open to home and overseas students. 

Home fees are covered. Eligible overseas students must make up the difference in tuition fee funding where funding is available.

Annual stipend provided: Research Council minimum rate (set by UKRI) £18,622 for 2023/24

How to apply 

Interested applicants should contact Dr Connah Kendrick  for an informal discussion. 

To apply you will need to complete the online application form for a full-time PhD  in Computing and digital technology (or download the PGR application form ).

You should also complete the PGR thesis proposal  (supplementary information) form addressing the project’s aims and objectives, demonstrating how the skills you have maps to the area of research and why you see this area as being of importance and interest.  

If applying online, you must upload your statement in the supporting documents section or email the application form and statement to [email protected] . Closing date 24 January 2024. Expected start date: April 2024.

Please quote the reference: SciEng-CK-2024-diabetic-foot-ulcer